# Section: Pages --- title: "About dbt Labs" description: "Explore dbt Labs' mission to transform data, meet the leadership team, and discover dbt's impact on analytics engineering and the data community." url: "https://www.getdbt.com/about-us" --- # About us dbt Labs is on a mission to empower data practitioners to create and disseminate organizational knowledge. [Read recent press releases](https://www.getdbt.com/blog/category/press) | [See open roles](https://www.getdbt.com/about-us/careers) *** Teams using dbt dbt Cloud Customers Certified Analytics Engineers dbt Community members *** ## Meet our Leadership Team ### Tristan Handy [object Object] ### Austin Stefani [object Object] ### Meg Pittman [object Object],[object Object],[object Object] ### Shawn Toldo [object Object],[object Object],[object Object] ### Drew Banin [object Object] ### Connor McArthur [object Object] *** ## Board of Directors ### Tristan Handy ### Connor McArthur ### Ashley Kramer ### Martin Casado ### Matt Miller *** ## Learn more about dbt Labs Explore more about who we are, what we build, and the impact our community is making. ### Latest news Get the latest news about dbt Labs with media mentions and press releases. [Read now](https://www.getdbt.com/press) ### See dbt in action Access customer case studies to see how organizations are using dbt Cloud to produce high-quality, reliable data. [Access case studies](https://www.getdbt.com/case-studies) ### About dbt Learn more about what dbt is and how it can help your team build trusted data, faster. [Learn about dbt](https://www.getdbt.com/product/dbt) *** ## Start deploying with dbt. Automate and scale your data pipelines effortlessly with dbt—from development to production. [Get started with dbt](https://www.getdbt.com/signup) | [Book your demo](https://www.getdbt.com/contact) --- --- title: "About dbt Labs - Careers" description: "Looking for a career in data? Join dbt Labs and work at the forefront of analytics engineering innovation." url: "https://www.getdbt.com/about-us/careers" --- # Come build with us at dbt Labs Join a remote-first company that's transforming the way the world does data. [See open roles](#roles) | [About our values](https://www.getdbt.com/about-us/values) *** dbt Labs + Fivetran: Building the Future of Data Together *** ## Why dbt Labs Support data teams everywhere with a company united by shared values (and Slack). dbt Labs is up-leveling the analytics profession through a workflow we call analytics engineering. If you want to build a career helping analysts build theirs, we’d love to meet you. ### Parental leave Take time to connect with your new family member. We happily provide 16 weeks of paid parental leave for new parents. ### Health insurance We provide high-quality medical, dental, and vision benefits to all employees and their dependents. ### Unlimited vacation Take a spontaneous trip or plan a dream staycation. Unlimited vacation means that you can stop budgeting your PTO. ### Retirement plan We contribute 3% (based on your salary) to your 401k plan. This is regardless of how much you decide to contribute. ### Flexibility We’re a distributed team and place a premium on trust. Communicate. Get your work done. Live your life. ### Learning and development We provide up to $500 per year to each employee to use on their own learning and development, however they see fit. --- --- title: "About dbt Labs - DEI" description: "Learn how dbt Labs fosters a culture of belonging, flexible work, transparent compensation, and career growth. Discover our DEI initiatives." url: "https://www.getdbt.com/about-us/dei" --- # Diversity, equity, and inclusion at dbt Labs *** ## Our commitment to belonging At dbt Labs, we bring our whole selves to work. We bring our interests and experiences, our cultural influences, our physical and emotional needs, our communication styles and lifestyles, our values, and our curiosity. We have built a lot of trust in each other, and we work hard to be worthy of it. The goal of our Diversity, Equity, and Inclusion (DEI) work at dbt Labs is to make sure everyone has a sense of belonging and the support they need to succeed. *** ## Flexibility and accessibility As an international team, we design our remote work culture to be flexible across time zones. - **39%** of us are caregivers - **10%** of us have a disability - **100%** of us have unpredictable lives We don’t expect everyone to be at every meeting. We prioritize written, asynchronous communication so you can contribute thoughtfully, when you’re at your best. You can handle personal responsibilities without missing something important or leaving your coworkers in the lurch. This culture is fed by our values of **We are human** and **We work hard and go home**. *** ## Equitable compensation and career growth At dbt Labs, we believe in pay transparency and equitable opportunity. We share salary ranges for open roles so that candidates have clear, upfront expectations. Internally, we review compensation and promotion outcomes every cycle to ensure fairness and proactively address any unintended disparities. Our compensation programs are designed to be market-driven, competitive, and sustainable, and we view career growth as a core part of retention. Internal mobility is actively encouraged, with clear guidelines and compensation aligned to scope and impact—not just tenure. Our goal is to recognize growth and make space for people to pursue their professional interests. Want to learn more about how we approach compensation and career development? Explore our [employee handbook](https://handbook.getdbt.com/docs/about_dbt_labs). Our compensation philosophy is grounded in our value of **Transparency always wins**, and our approach to career growth is shaped by our belief in **Moving up the stack**—giving every employee a clear path to learn, advance, and lead. *** ## In the media ### Inside dbt Labs’ Efforts To Make Conferences Accessible To Everyone, Inside And Out ### Pride Month at dbt Labs: LGBTQ+ Identity at work ### 16 Companies With the Best Diversity and Inclusion Programs ### Empowered to Be Human: 5 Ways to Spot a Person-First Company *** ## Let's build together dbt Labs is on a mission to empower data practitioners to create and disseminate organizational knowledge. Come see how you fit in. [See open roles](https://www.getdbt.com/about-us/careers) | [About dbt Labs](https://www.getdbt.com/about-us) --- --- title: "About dbt Labs - Values" description: "Discover the core values that drive dbt Labs, from transparency and diversity to long-term growth, ensuring value creation for the data community." url: "https://www.getdbt.com/about-us/values" --- # Our values Initially penned before the company was even founded, our values have been the foundation on which we've built a company, and a movement. [See our open roles](https://www.getdbt.com/about-us/careers) | [See our leadership principles](#leadership-principles) *** ### We are a mission-driven company. We believe that profits are an important tool in the pursuit of our mission, but they are not the mission itself. ### We are more concerned with value creation than value capture. We will only succeed if we create value in the world. If we optimize for that first, commercial success will follow. ### Work done well is its own end. We do great work because it is an expression of who we are, a contribution of our unique talents and perspectives to a purpose larger than ourselves. Work done well creates ripples in the pond. ### We contribute to the knowledge loop. The highest goal of any human is to produce new knowledge that can subsequently be built upon by others. This is the process upon which every good thing in human society has been built. We participate in this most fundamental of human endeavors by thinking in public and defaulting to open source. ### Transparency always wins. There are countless examples of choices that we all have in our professional lives of just how honest we want to be. We choose to be completely honest, even when that is uncomfortable, or even when it would lead to short-term negative consequences. We believe that transparency is a north star, and that acting transparently is always in the long-term best interests of achieving our mission. ### We value diversity. People with different mindsets and experiences, working together, create better outcomes. This includes diversity of race and gender, as well as the diversity of academic backgrounds, socio-economic backgrounds, geographic backgrounds, ideologies, and interests. ### Users are our best advocates. We market our products and services by working with amazing humans, making them incredibly happy, and asking them to spread the word. We go above and beyond for our clients / users to invest in our future growth. ### We are humble. While we believe that we are building something exceptional, that knowledge does not make us feel proud, it makes us feel humble. It imbues us with a deep sense of responsibility towards our clients, coworkers, and the community at large. ### We work hard and go home. We are here to build something great—and we recognize the hard work and sacrifice that entails!—but work isn’t our entire identity. We are parents and children and siblings and friends and citizens and humans. These other identities matter to us! And to create space for them, we both accept the responsibility of creating our own individual boundaries and work to support the boundaries that others have set for themselves. ### We are human. We are human beings innovating in a shared service to a mission. We structure our compensation and benefits, work hours and location policies, work and management styles, and employee agreements to support this fundamental human-ness. We bring our whole selves to work, and we recognize that our identities extend beyond the work that we do. ### We believe in moving up the stack. We believe that all team members should seek to replace themselves on an ongoing basis by building processes, technology, and documentation that obviate their existing work. We have an abundance mindset: there is always more, and more valuable, work to do. Moving up the stack presents growth opportunities for both the individual and the team. ### We optimize for the long-term. While we pursue the mission with intense focus, we recognize that creating the change in the world that we wish to see will not happen overnight. We think, plan, and act for the long-term. ### Values are more important than success. We are not interested in success absent the values in this document. We have strongly held opinions on how a company should be built and these are non-negotiable. We do not believe that these opinions are an absolute truth, but they are an absolute truth for us. *** ## Our leadership principles Our values are special, and they’ve guided us since dbt Labs was Fishtown Analytics. They are our core beliefs, and demonstrate our character as a company. They influence our culture, and we expect every team member to demonstrate internally and externally. Our leadership principles are scoped for current and aspiring leaders. They articulate how we show up, as well as how we can be held accountable and hold others accountable. These principles should guide folks in how they make decisions and how they manage their teams. They are specific and actionable. They shape our leaders, team dynamics and strategic direction. ### We create remarkable experiences. Every touch point with dbt Labs should be remarkable—for customers, for community members, for employees, and for every other stakeholder of the business. Leaders are allergic to mediocrity, and hire and coach their teams to envision, identify, and create the remarkable. ### We are customer-obsessed. Leaders start with the customer and work backwards. They work vigorously to earn and keep customer trust. Although leaders pay attention to competitors, they obsess over customers. ### We drive results. Leaders deeply understand how value is created and relentlessly focus on it. Despite setbacks, changes, and challenges, leaders rise to the occasion and deliver outcomes for our customers and for the business. We solve problems, exceed expectations and amplify the impact of those around us. ### We are pleased, but not satisfied. While we are proud of what we’ve accomplished, leaders prefer to focus on how much more there is to do in service of our mission and our customers. We do not rest on our laurels. We push ourselves and each other to be better every day. ### We earn trust. Leaders know that trust is the single most valuable asset that any group of humans can have, and we know that building trust requires work. We do that work day-in, day-out, with our customers, our teams, and our peers. We are authentic, listen to be wrong, and live up to our commitments. ### We have a bias for action. Speed matters in business, and it is one of our strengths. Leaders help teams move quickly by setting pace, energy, and context and by making good decisions quickly. We take calculated risks while learning quickly from our failures. Leaders only slow down a decision when we are faced with a one-way-door. ### We are owners. Leaders never take off their owners hat. We act on behalf of our entire company, not just our own team. We spend the company’s money as if it were our own. We take ownership for both good and bad outcomes. We never sacrifice long term value for short term results. ### We are self-aware. Leaders need to have a clear understanding of their own skills, abilities, behaviors and areas for improvement. They recognize and compensate for their weaknesses, biases, and blind spots. They understand how their actions impact others. Leaders embrace challenging feedback as an opportunity to build self-awareness. ### We debate and decide. Leaders lean into debate and work to disconfirm our own beliefs. We find the most credible people who disagree with us and try to understand their reasoning. We support our fellow leaders by asking hard questions and disagreeing in public. Ultimately, leaders make decisions, at which point the organization as a whole commits to moving forwards. ### We have fun. Leaders know that humans only come together to produce remarkable results when there is a spark of fun. They work to inject fun—and their own idiosyncratic human selves!— into their work and their teams. *** ## Learn more about dbt Labs Explore more about who we are, what we build, and the impact our community is making. ### Latest news Get the latest news about dbt Labs with media mentions and press releases. [Read now](https://www.getdbt.com/press) ### See dbt in action Access customer case studies to see how organizations are using dbt Cloud to produce high-quality, reliable data. [Access case studies](https://www.getdbt.com/case-studies) ### About dbt Learn more about what dbt is and how it can help your team build trusted data, faster. [Learn about dbt](https://www.getdbt.com/product/dbt) *** *The dbt Community* ## Join the largest community shaping data The dbt Community is your gateway to best practices, innovation, and direct collaboration with thousands of data leaders and AI practitioners worldwide. Ask questions, share insights, and build better with the experts. [Join the Community](https://www.getdbt.com/community/join-the-community) | [Explore the Community](https://www.getdbt.com/community) --- --- title: "Brand Guidelines" url: "https://www.getdbt.com/brand-guidelines" --- # Brand guidelines All usage of dbt Labs™ logo marks is governed by our Trademark Policy. Assuming you have permission, this page will provide further detail on how to use our logo marks. [Download brand assets](https://cdn.sanity.io/files/wl0ndo6t/main/0ea2ccef348a2014d2a38fa63bf7c23fb898a448.zip) | [Read policy](https://www.getdbt.com/trademark-guidelines) *** ## dbt Logos The guidelines in this document apply to all dbt logo marks. These logos communicate unique aspects of the dbt brand, please choose the appropriate logo: - Use dbt Labs when referring to the company that creates and maintains dbt - Use dbt when referring to the total dbt software, both commercial and open source. All dbt logos can be shown in either black or white logotype. Select the version that will provide the highest contrast. --- --- title: "dbt Analytics Engineering Certification Exam" description: "Validate your dbt skills by earning the analytics engineer certification." url: "https://www.getdbt.com/certifications/analytics-engineer-certification-exam" --- # dbt Analytics Engineering Certification Exam The Analytics Engineering Certification Exam evaluates your ability to build, test, and maintain models for data accessibility while using dbt to apply engineering principles to analytics infrastructure. [Register now](https://pages.talview.com/dbtlabs/certifications/) *** *Supported version - 1.11 * Duration Questions Passing score Price *** ## Certification exam overview Earning your certification is an important step in demonstrating your expertise. To set yourself up for success, it's recommended that you have SQL proficiency and at least six months of experience working with dbt or dbt Core. This foundational knowledge will help you navigate the exam confidently. To help you prepare, the exam guide provides a detailed breakdown of [what's covered](https://www.getdbt.com/certifications/analytics-engineer-certification-exam#faq), along with [sample questions](https://www.getdbt.com/certifications/analytics-engineer-certification-exam#sample-questions) and a [study guide](https://www.getdbt.com/dbt-assets/certifications/dbt-certificate-study-guide-version-1-11). Once you feel ready, you can register and schedule your exam at a convenient time. [Register now](https://pages.talview.com/dbtlabs/certifications/) *** ## What's covered in the exam? ### Developing and optimizing dbt models - Identifying and verifying any raw object dependencies - Understanding core dbt materializations - Conceptualizing modularity and how to incorporate DRY principles - Using commands such as `build, run, test, docs, show, snapshot,` and `seed` - Creating a logical flow of models and building clean DAGs - Defining configurations in `dbt_project.yml` - Using dbt Packages - Creating Python Models - Providing access to users to models with the “grants” config - Creating snapshots in YAML - Selecting the optimal incremental strategy based on a dataset's characteristics - Validating model logic and schema definitions in dry-runs using the --empty flag - Running models in sample mode using the --sample flag - Understanding advanced dbt materializations such as microbatch ### Managing dbt models governance - Adding contracts to models to ensure the shape of models - Creating different versions of our models and deprecating the old ones - Defining constraints in YAML to enforce data integrity at the platform level ### Debugging data modeling errors - Understanding logged error messages - Troubleshooting using compiled code - Troubleshooting .yml compilation errors - Developing and implementing a fix and testing it prior to merging - Managing dbt behavior with flags ### Troubleshooting and optimizing dbt pipelines - Troubleshooting and managing failure points in the DAG - Using dbt clone ### Implementing dbt tests - Using generic, singular, custom, and custom generic tests on a wide variety of models and sources - Testing assumptions for dbt models and sources - Implementing various testing steps in the workflow ### Implementing and Maintaining External Dependencies - Implementing dbt exposures - Implementing source freshness ### Leveraging the dbt state - Understanding state and state selection - Using dbt retry *** ## Sample Questions ### Questions 1 ### Questions 2 ### Questions 3 ### Questions 4 ### Questions 5 ### Questions 6 ### Questions 7 ### Questions 8 ### Questions 9 ### Questions 10 *** ## Ready to Get Certified? Validate your dbt expertise and earn your certification. Get started today. [Register now](https://pages.talview.com/dbtlabs/certifications/) --- --- title: "dbt Architect Certification Exam" description: "Validate your ability to design secure, scalable dbt implementations with the dbt architect certification exam." url: "https://www.getdbt.com/certifications/dbt-architect-certification-exam" --- # dbt Architect Certification Exam The dbt Architect exam assesses your ability to design secure, scalable dbt implementations, with a focus on environment orchestration, role-based access control, integrations with other tools, and collaborative development workflows aligned with best practices. [Register now](https://pages.talview.com/dbtlabs/certifications/) *** Duration Questions Passing score Price *** ## Certification exam overview Earning your certification is an important step in demonstrating your expertise. To set yourself up for success, it's recommended that you have SQL proficiency and at least six months of experience administrating an Enterprise dbt account. This foundational knowledge will help you navigate the exam confidently. To help you prepare, the exam guide provides a detailed breakdown of [what's covered](https://www.getdbt.com/certifications/dbt-architect-certification-exam#faq), along with [sample questions](https://www.getdbt.com/certifications/dbt-architect-certification-exam#sample-questions) and [a study guide](https://www.getdbt.com/dbt-assets/dbt-certificate-study-guide-for-cloud-architect). Once you feel ready, you can register and schedule your exam at a convenient time. [Register now](https://pages.talview.com/dbtlabs/certifications/) *** ## What's covered in the exam? ### Configuring dbt data warehouse connections - Understanding how to connect the warehouse - Configuring IP whitelist - Creating and testing a connection for the project - Authenticating through OAuth to access the data in IDE - Adding Client ID and Secret for OAuth ### Configuring dbt git connections - Connecting the git repo to dbt - Setting up integrations with git providers ### Creating and maintaining dbt environments - Understanding access control to different environments - Determining when to use a service account - Rotating key pair authentication via the API - Understanding environment variables - Creating new dbt deployment environment - Setting default schema / dataset for environment - Understanding custom branches and which to configure to environments - Configuring dbt to allow deferral to other environments - Adding credentials to deployment environments to access warehouse for production / CI runs ### Creating and maintaining job definitions - Setup a CI job with deferral - Understanding steps within a dbt job - Scheduling a job to run on schedule - Implementing run commands in the correct order - Creating new dbt job - Configuring optional settings such as environment variable overrides, threads, deferral, target name, and dbt version override - Generating documentation on a job that populates the project's doc site - Configuring jobs to be triggered after other dbt jobs (job chaining) - Configuring Advanced CI - Configuring self deferral - Understanding when to use which type of job deferral ### Configuring dbt security and licenses - Creating Service tokens for API access - Assigning permission sets - Creating license mappings - Adding and removing users - Adding SSO application for dbt enterprise - Creating and assigning RBAC ### Setting up monitoring and alerting for jobs Setting up email notifications Using Webhooks for event-driven integrations with other systems ### Setting up a dbt mesh and leveraging cross project references - Setting up additional dbt projects - Understanding how environment types relate to cross project references\ - Utilizing model governance ### Configuring and using dbt Catalog - Using dbt Catalog to understand the current lineage, troubleshoot issues and optimize cost and performance - Using dbt Catalog to find public models and cross project references *** ## Sample Questions ### Question 1 ### Question 2 ### Question 3 ### Question 4 ### Question 5 ### Question 6 ### Question 7 ### Question 8 ### Question 9 ### Question 10 *** ## Ready to Get Certified? Validate your dbt expertise and earn your certification. Get started today. [Register now](https://pages.talview.com/dbtlabs/certifications/) --- --- title: "Legal - Privacy Policy" description: "Learn how dbt Labs collects, uses, and safeguards your personal information across our website, services, and communications." url: "https://www.getdbt.com/cloud/privacy-policy" --- # dbt Labs Privacy Policy *** Last updated: June 11, 2025 This privacy policy for dbt Labs, LLC (together with our affiliates, “**dbt Labs**”, “**we**”, “**our**”, or “**us**”) discloses how we collect, store, process, transfer, share, hold, and use data that identifies or is associated with visitors (“**personal information**”) to our public website at [https://www.getdbt.com](https://www.getdbt.com/) (“**website**”) and any other personal information you otherwise provide to us as further described below. For the purposes of this privacy policy, “**you**” and “**your**” means you as the Visitor. We are a company established under Delaware State law in the United States with a registered office at 1221 Broadway, Suite 2400, Oakland, CA 94612, and for the purposes of General Data Protection Regulation (“**GDPR**”) and the GDPR as implemented in the UK (together referred to as the “**EU and UK Data Protection Laws**”), we are the data controller. This privacy policy does not cover information submitted to us as part of your use of the dbt platform including, but not limited, to information about a client’s customers or authorized users. This privacy policy also does not cover information of people whose only contact with us is visiting our [dbt Community Slack](https://www.getdbt.com/community/join-the-community/). Notwithstanding the foregoing, this policy covers individuals who communicate with us (other than via the dbt platform), log into the dbt website(s), attend an event, complete a form, use website services including the dbt Extension for Visual Studio Code ("Plugin"), and/or provide personal information other than for dbt platform authentication purposes. To the extent we process your personal information on your behalf or under your instructions, we are the data processor and/or service provider, and such processing is subject to our data processing agreement found at [https://www.getdbt.com/dbt-assets/cloud/dpa](https://www.getdbt.com/dbt-assets/cloud/dpa) unless superseded by an agreement executed by both you and dbt Labs. Aside from these circumstances, dbt Labs is the data controller of the personal information we hold about you. Our website provides valuable information meant to enable efficiency, accuracy and best practices in your data transformations. Before accessing or using our website or otherwise providing us your personal information, please ensure that you have read and understood our collection, storage, use and sharing of personal information about you as described in this privacy policy. If you do not want information about you used as described in this privacy policy, then please do not provide your personal information to us. **1. PERSONAL INFORMATION WE COLLECT ABOUT YOU AND HOW WE USE AND SHARE IT** _Information you give to us_ - We collect personal information when you voluntarily submit such information directly to us. This can include information you provide to us when you connect with us by filling in a form or entering information on our website, logging into our website services without SSO, corresponding with us by phone, email, chat assistant, or otherwise, subscribing to our mailing lists, blogs, newsletters or other forms of marketing communications, visiting our public pages including source code, documentation and repositories, registering for and/or attending, virtually or in-person, one of our many trainings, international meet-ups, booth locations, or our Coalesce Analytics Engineering Conference, responding to a survey, completing an online form, downloading the Plugin and selecting to send us information, completing an online form, or entering a promotion (“Connections”). - The table at Annex 1 specifies the categories of personal information we collect about you, within the past 12 months, the purpose for collection, and how we use and/or disclose that information. To the extent applicable under EU, Swiss, and UK Data Protection Laws, the table also lists the legal basis which we rely on to process personal information, the categories of recipients that we share personal information with and the criteria by which we determine applicable retention periods. _Information we collect from third parties_ - This privacy policy governs any personal information we receive from Visitors. We are not responsible or liable for the accuracy of the information provided to us by Visitors and are not subject to any third party’s policies or practices. See Sections 8, 9 and 10, and the Annexes below for more information. - The table at Annex 1 sets out the categories of personal information we collect about you and how we use and disclose that information in the past 12 months. To the extent applicable under EU and UK Data Protection Laws, the table also lists the legal basis which we rely on to process the personal information, the categories of recipients that we share personal information with and the criteria that we use to determine applicable retention periods. _Information we collect automatically_ - We also automatically collect personal information about you indirectly about how you access and use the website, such as information about the device you use to access the Connections. - We automatically collect telemetry and authentication data from the Plugin for the purpose of providing, supporting, maintaining, updating, improving, and optimizing the Plugin and its performance. Authentication data may include name, email, and device identifications. This minimal personal data is necessary for appropriate security. Telemetry data utilizes our standard security practices including encryption in transit and at rest. We collect and analyze Plugin usage and performance data to gain insights about its performance. This may encompass a broad range of data collection and analysis as necessary to understand Plugin-related user behavior, evaluate system performance, and identify areas for improvement. More specifically, telemetry data may include operating systems and device identifications, run times and other performance metrics, events and errors, response times, and memory usage. It may be used by us to identify performance issues, optimize features, prioritize feature development, troubleshoot, validate updates, or improve security. The Plugin is further described at [https://docs.getdbt.com/docs/about-dbt-extension](https://docs.getdbt.com/docs/about-dbt-extension). - The table at Annex 2 sets out the categories of personal information we collect about you automatically and how we use and disclose that information in the past 12 months. To the extent applicable under EU and UK Data Protection Laws, the table also lists the legal basis which we rely on to process the personal information, the categories of recipients that we share your personal information with and the criteria that we use to determine applicable retention periods. - We may consider personal information collected about you and how many and the types of Connections we have with you in order to predict what products or services may be the best fit for you. This allows us to tailor our marketing efforts and create the best personalised experience. We may use third party tools to assist us and manage our processes. More information about what we collect and how we use the personal information is in the Annexes. - We may anonymise and aggregate any of the personal information we collect (so that it does not directly identify you). We may use anonymised information for purposes that include testing our IT systems, research, incorporation of Privacy by Design principles, data analysis, improving our products and services and developing new products and features. We may also share such anonymised information with others. - If you choose not to provide personal information, we may not be able to respond to your requests. _Information we collect at events_ - We collect personal information you give us related to registration. This may be shared with event organizers, sponsors, venues, or providers of services for the event for purposes of planning for, hosting, and administering events, and of communicating about products and services and future events. We may also collect personal information related to your attendance, the sessions you attend, your sessions as speaker or facilitator, and your other activities. - We may collect and share on our website personal information related to your attendance, speaking, facilitating or participation in discussions/talks/networking that includes records of your image, voice, and commentary for the purpose of documentation of the event, facilitating remote attendance, website accuracy, and for the participation and education of online participants such as those with health, travel or other constraints. **2. MARKETING AND ADVERTISING** From time to time we may contact you with information about our products and services. Most marketing messages we send will be by email. For some marketing messages, we may use personal information we collect about you to help us determine the most relevant marketing information to share with you, and we may tailor advertising to you based on the information we’ve collected in an effort to provide you with information that is the most relevant and useful to you. We may use third party tools as part of our processes, but we share very limited personal information with them, and they are under contractual obligations to only use data we share on our behalf and in compliance with applicable law. We use OneTrust to permit Visitors in certain jurisdictions to opt-in or opt-out of Google analytics, Optimizely analytics, and marketing messages from us in compliance with applicable law, and you may indicate your preferences on forms we use when we first collect your contact details. You can effectuate this by opening the ‘Preference Center’ (click the link in the banner or footer) and making sure all toggles are off (aside from strictly necessary which are always enabled). You can also change your marketing preferences at a later date by clicking on the unsubscribe link at the bottom of our marketing emails. **3. DATA SECURITY** We implement technical and organisational measures designed to protect personal information about you against accidental or unlawful destruction, loss, change or damage. However, please be aware though that, despite our best efforts, no security measures are perfectly secure, error-free, or impenetrable, and we cannot guarantee “perfect security.” Any information you send to us electronically may not be secure when it is transmitted to us. We recommend that you do not use unsecure channels to communicate sensitive or confidential information to us. Any information you send us through any means is transmitted at your own risk. **4. INTERNATIONAL TRANSFERS OF YOUR PERSONAL INFORMATION** If you are located in the EU or EEA, UK, or Switzerland, this may mean that your personal information will be stored or processed in the USA. To the extent an EU-US, UK-US and/or Swiss-US adequacy ruling is in place, we maintain the obligations identified in Section 6 below. In the absence of an adequacy ruling and Data Privacy Framework certification, the following obligations apply: - When transferring personal information originating from the EEA or the UK to the USA, we seek to comply with applicable EU and UK Data Protection Laws by using (i) the European Commission’s model contracts for the transfer of personal information to third countries (i.e., the standard contractual clauses) (the “**Model Clauses**”); (ii) the equivalent contract issued by the relevant competent authority of the UK, Switzerland or another country, as relevant; or (iii) appropriate derogations for specific situations pursuant to Article 49(1) of the GDPR and UK GDPR – unless the data transfer is to a country that has been determined by the European Commission and/or the relevant UK or other governmental authorities, as applicable, to provide an adequate level of protection for personal information. - If you wish to enquire further about the safeguards we use or to examine a copy of the Model Clauses, please contact us using the contact details set out at the end of this privacy policy. **5. YOUR RIGHTS IN RESPECT OF PERSONAL INFORMATION ABOUT YOU** - **EU/UK.** Where applicable, in accordance with applicable EU, Swiss, and UK Data Protection Laws, if you are located in the EEA, Switzerland, or the UK, you may have the following rights in respect of personal information about you that we hold: - _Transparent Communications._ Communications will be concise, transparent, intelligible and easily accessible form, using clear and plain language (Art. 12 of the GDPR). - _Disclosure upon Collection._ The collector of the data will, at the time when personal data are obtained, provide the data subject with information related to the collector including contact details, the purposes for the collection, the legal basis, and the third party and location of any data transfers (Art. 13 of the GDPR). - _Notice and Access._ The right to receive notice that your data is in a data collector’s possession and identify the source of the data (Art. 14 of the GDPR) and to obtain access to your personal information, to understand how we use it, and who we share it with (Art. 15 of the GDPR). - _Rectification._ The right to obtain rectification of your personal information where that personal information is inaccurate or incomplete (Art. 16 of the GDPR) and may request notice be given to data recipients downstream (Art. 19 of the GDPR). - _Erasure._ The right to obtain the erasure of your personal information in certain circumstances, such as where the personal information is no longer necessary in relation to the purposes for which it was collected or processed (Art. 17 of the GDPR) and may request notice be given to data recipients downstream (Art. 19 of the GDPR). - _Restriction._ The right to require us to stop processing the personal information we hold about you, other than for storage purposes, in certain circumstances (Art. 18 of the GDPR). - _Portability._ The right to receive a copy of the personal information we hold about you and to request that we transfer it to a third party, in certain circumstances and with certain exceptions (Art. 20 of the GDPR). - _Object._ The right to object to our processing of your personal information (Art. 21 of the GDPR). - _Objection to marketing._ The right to object to marketing at any time by clicking the unsubscribe button at the bottom of the email (Art. 21 of the GDPR). - _Withdrawal of Consent._ To the extent that we rely on consent to process personal information about you, the right to withdraw this consent at any time by clicking the unsubscribe button at the bottom of the email (Art. 21 of the GDPR). - _No Profiling._ The right not to be subject to a decision based solely on automated processing, including profiling, which produces legal effects concerning him or her or similarly significantly affects him or her without consent (Art. 22 of the GDPR). This list is not meant to be a complete statement of your rights, does not constitute legal advice, nor is it a guarantee of such rights. The list is subject to change, revision, regulation, court decision, interpretation, or restriction (Art. 23 of the GDPR) by governmental authorities. Please note that a number of these rights only apply in certain jurisdictions or circumstances. The rights are subject to being balanced against other factors or rights, and may be impacted where fulfilling your request would adversely affect other individuals or our trade secrets/ intellectual property, where there are overriding public interests or where we are required by law to retain your personal information. If you wish to exercise one of these rights, please contact us using the contact details at the end of this privacy policy. To further protect your rights, we may need to request verification of your identity pursuant to the process disclosed under the Identity Verification section below. You may also review and edit the personal information you have submitted to us by logging into your account on our website. If you have complaints about how we process personal information about you, please contact us at the details provided at the end of this privacy policy and we will respond to your request as soon as possible. You may also have the right to make a complaint to the relevant Supervisory Authority in the EEA country in which you live or work, or with the UK Information Commissioner’s Office, as applicable to you. A list of Supervisory Authorities is available here: [https://edpb.europa.eu/about-edpb/about-edpb/members_en](https://edpb.europa.eu/about-edpb/board/members_en)[.](https://www.theatlantic.com/) - **California**. Where applicable, if you are a California resident you may have the following rights under the California Consumer Privacy Act of 2018 (the “**CCPA**”) in relation to “personal information” we have collected about you as defined in the CCPA; these rights are, to the extent required by the CCPA and subject to verification and any applicable exception: - _Know/Access._ You have the right to know, which lets you request that we disclose certain information to you about our collection and use of certain personal information about you as described below: - the specific pieces of personal information collected; - the categories of personal information collected; - the categories of sources from whom the personal information is collected; - the purpose for collecting the personal information; and - the categories of third parties with whom we have shared the personal information. - _Delete._ You have the right to request that we delete the personal information. - _Opt Out._ You have the right to opt out of the sale or sharing of your personal. We do not sell your personal information or share it, although we may share it with third parties who use it to provide us services and are our service providers. - _Rectification._ You have the right to correct inaccurate information a business has on you. - _Restriction._ You have the right to limit the use and disclosure of sensitive personal information. - _Freedom from Discrimination._ You have the right to be free from unlawful discrimination for exercising any of the rights above. - To request your exercise of the rights described above, please submit a request to us by emailing us at privacy@dbtlabs.com. These rights may be subject to exceptions, limitations, interpretations, or modifications by applicable law. - To further protect your rights, we may request verification of your identity pursuant to the process disclosed under the Identity Verification section below. You may also review and edit the personal information you have submitted to us by logging into your account on our website. - **Virginia Residents**.As the controllers of personal information you have provided to us, we provide the following privacy notices specific to Virginia residents only: - The categories of and purpose for processing personal data are in Annex 1, which also contains the categories of personal data; - We may process your personal information in accordance with Section 1.7 which may include targeted advertising to personalize your online experience with subjects of interest to you. To opt-out, please contact us using the contact details at the end of this privacy policy; - We will implement and maintain reasonable data security practices to protect the confidentiality, integrity, and accessibility of personal data and only hold the data for the specific purpose indicated above and for only as long as necessary to achieve the purpose (purpose limitation and data minimization); - The categories of personal data we share with third parties and the categories of such third parties are in Annex 1 and Annex 3; - You may make a personal data requests of us; and - To exercise your consumer rights or appeal a decision with regard to your request, please contact us using the contact details at the end of this privacy policy. These rights may be subject to exceptions, limitations, interpretations, or modifications by applicable law. - To further protect your rights, we may request verification of your identity pursuant to the process disclosed under the Identity Verification section below. You may also review and edit the personal information you have submitted to us by logging into your account on our website. Virginia residents may have the following personal data rights: - _Know._ You have the right to be informed (right to know) of the processing of personal data; - _Access._ You have the right to access their personal information; - _Rectify._ You have the right to correct inaccurate personal data; - _Opt-Out_. You have the right to opt out of the sale of personal data targeted advertising, or profiling; and - _Deletion._ You have the right to deletion of personal data. Identify Verification. Where applicable law permits us to verify identity: - To further protect your rights, we may request verification of your identity including your name, email address, IP Address, country of residence, and/or other contact information, your account identification, and the company brand with which you have or had a relationship related to the applicable account prior to addressing your request, and we may ask for additional information and documents prior to fulfilling your request. - You may be entitled, in accordance with applicable law, to submit a request through an authorized agent. Only you, or someone legally authorized to act on your behalf, may make a verifiable consumer request, data access request, or other exercise of privacy rights related to personal information collected about you. To designate an authorized agent to exercise your rights and choices on your behalf, please provide your authorized agent with signed, written permission demonstrating that they have been authorized by you to act on your behalf. You may be required to either verify your own identity directly with us; or provide us a copy of the written permission authorizing the agent to submit the request. - We may be contractually or legally obligated to provide notice of your request to the company brand with which you have or had a relationship related to the applicable account prior to addressing your request. - We may compare personal information submitted as part of the request and/or identity verification process to related account information or information available to us through your logging into your account on our website. - If we cannot identify you, we may be obligated to refuse the request. **6. JURISDICTION AND ENFORCEMENT** - dbt Labs complies with the EU-U.S. Data Privacy Framework program (EU-U.S. DPF), and United Kingdom (and Gibraltar) Extension to the EU-U.S. DPF, and the Swiss-U.S. Data Privacy Framework program as set forth by the U.S. Department of Commerce (EU, UK and Swiss collectively, the DPF). dbt Labs has certified to the U.S. Department of Commerce that it adheres to the EU-U.S. Data Privacy Framework Principles with regard to the processing of personal data received from the European Union and the UK (including Gibralter) in reliance on the EU-U.S. and UK DPFs. dbt Labs has certified to the U.S. Department of Commerce that it adheres to the Swiss-U.S. Data Privacy Framework program Principles (Swiss-U.S. DPF Principles) with regard to the processing of personal data received from Switzerland in reliance on the Swiss-U.S. DPF. If there is any conflict between the terms in this privacy policy and the EU-U.S. DPF Principles and/or the Swiss-U.S. DPF Principles (collectively, Principles), the applicable Principles shall govern. To learn more about the Data Privacy Framework (DPF) program, and to view our certification, please visit [https://www.dataprivacyframework.gov/](https://www.dataprivacyframework.gov/). The Data Privacy Framework supersedes and replaces the US Privacy Shield. - With respect to data transferred pursuant to the Data Privacy Framework (DPF) program, dbt Labs - does not collect sensitive personal information (i.e., personal information specifying medical or health conditions, racial or ethnic origin, political opinions, religious or philosophical beliefs, trade union membership or information specifying the sex life of the individual); and - does not use personal information for a purpose that is materially different from the purpose(s) for which it was originally collected or subsequently authorized by the individuals. - Pursuant to the DPF, EU, UK, and Swiss individuals have the right to obtain our confirmation of whether we maintain personal information relating to you in the United States. You may also request access to that data for the purpose of verifying, updating or correcting inaccurate information. Furthermore, you can request erasure of information handled in violation of the DPF Principles. We will provide an individual opt-in for individuals identifiably from the EU, UK and Switzerland before we share your data with third parties (other than our agents). - dbt Labs is responsible for the processing of personal data it receives pursuant to the DPF and to the extent it subsequently transfers such data to a third party acting as an agent on its behalf. To the extent any individual’s personal information is disclosed to a third party, such personal information is made only to third parties (i) under contract with dbt Labs, and (ii) acting as agents of dbt Labs, i.e., performing task(s) on behalf of and under the instructions of dbt Labs. - dbt Labs complies with the DPF Principles for all onward transfers of personal data from the EU, the United Kingdom, and Switzerland, including applicable onward transfer liability provisions. - With respect to personal data received or transferred pursuant to DPF , dbt Labs is subject to the regulatory investigative and enforcement powers of the U.S. Federal Trade Commission. In certain situations, dbt Labs may be required to comply with applicable law in disclosing personal data in response to lawful requests by public authorities, including to meet national security or law enforcement requirements. - In compliance with the EU-US, UK and Swiss-Data Privacy Framework Principles, dbt Labs commits to resolve complaints about your privacy and our collection or use of your personal information. European Union, United Kingdom, or Swiss individuals with DPF inquiries or complaints regarding this privacy policy should first contact dbt Labs using the contact details at the end of this privacy policy. - We have further committed to refer unresolved privacy complaints under the DPF Principles to an independent dispute resolution mechanism, Data Privacy Framework Services, operated by BBB National Programs, a non-profit alternative dispute resolution provider based in the United States. If you do not receive timely acknowledgment of your complaint, or if your complaint is not satisfactorily addressed, please visit [https://bbbprograms.org/programs/all-programs/dpf-consumers/ProcessForConsumers](https://bbbprograms.org/programs/all-programs/dpf-consumers/ProcessForConsumers) for more information and to file a complaint. This service is provided free of charge to you. - If your DPF complaint cannot be resolved through the above channels, under certain conditions, you may invoke binding arbitration for some residual claims not resolved by other redress mechanisms. See [https://www.dataprivacyframework.gov/framework-article/ANNEX-I-introduction](https://www.dataprivacyframework.gov/framework-article/ANNEX-I-introduction). **7. COOKIES AND SIMILAR TECHNOLOGIES** - We also automatically collect information including personal information and details including your interaction with the website. To do this, we may use cookies, web beacons/clear gifs, and other similar technologies. - We use the following types of cookies: - _Strictly necessary cookies._ These are cookies required for the operation of our website. They include, for example, cookies that enable you to log into secure areas of our website or make use of e-billing services. - _Analytical/performance cookies._ They allow us to recognise and count visitors moving around our website. This helps us to improve the way our website works, for example, by ensuring that Visitors are finding what they are looking for easily. For example, we may use Mouseflow, HotJar, or other third-party analytics tools, to track page content and click/touch, movement, scroll and keystroke activity. With respect to Hotjar (and any other third-party analytics tools listed in Annex 3), we use it in order to better understand our users’ needs and to optimize our services and user experiences. Hotjar is a technology service that helps us better understand our users’ experience (e.g. how much time they spend on which pages, which links they choose to click, what users do and don’t like, etc.) and this enables us to incorporate user feedback and usage patterns into our services. Hotjar uses cookies and other technologies to collect data on our users’ behavior and their devices. This may include a device’s IP address (processed during your session and stored in a de-identified form), device screen size, device type (unique device identifiers), browser information, geographic location (country only), and the preferred language used to display our website. Hotjar stores this information on our behalf in a pseudonymized user profile. Hotjar is contractually forbidden to sell any of the data collected on our behalf. For further details about Hotjar, please contact Hotjar at https://help.hotjar.com/hc/en-us/requests/new or, to stop Hotjar from collecting your data, please see the Data Privacy page at https://help.hotjar.com/hc/en-us/articles/360002735873-How-to-Stop-Hotjar-From-Collecting-your-Data. - _Functionality cookies._ These are used to recognise you when you return to our website. This enables us to personalise our content for you, greet you by name and remember your preferences (for example, your opt-out or preferred language). - _Targeting cookies._ These cookies record your visit to our website, the pages you have visited and the links you have followed. We will use this information to make our website, the advertising displayed on it, and the marketing messages we send to you more relevant to your interests. We may also share this information with third parties who provide a service to us for this purpose. - _Third party cookies._ Please be aware that advertisers and other third parties may use their own cookies tags when you click on an advertisement or link on our website. These third parties are responsible for setting out their own cookie and privacy policies. - Annex 3 contains more information about the cookies we use and how long they remain on your device. Annex 3 is updated and refreshed monthly. - The cookies we use are designed to help you get the most from the website, such as to distinguish you from other Visitors of our website. This helps us to provide you with a good experience when you browse our website and also allows us to improve our website, but if you do not wish to permit cookies, most browsers allow you to change your cookie settings. Please note that if you choose to refuse cookies you may not be able to use the full functionality of our website. These settings will typically be found in the “options” or “preferences” menu of your browser. In order to understand these settings, the following links may be helpful, otherwise you should use the “Help” option in your browser for more details. - Cookie settings in Internet Explorer [https://support.microsoft.com/en-us/products/windows](https://support.microsoft.com/en-us/products/windows) - Cookie settings in Firefox [http://support.mozilla.org/en-US/kb/cookies](http://support.mozilla.org/en-US/kb/cookies) - Cookie settings in Chrome [https://support.google.com/chrome/answer/95647?hl=en](https://support.google.com/chrome/answer/95647?hl=en) - Cookie settings in Safari on the web [https://support.apple.com/kb/PH5042?locale=en_GB](https://support.apple.com/kb/PH5042?locale=en_GB) and iOS [https://support.apple.com/en-gb/HT201265](https://support.apple.com/en-gb/HT201265) - If you only want to limit third party advertising cookies, you can turn such cookies off by visiting the following links (please bear in mind that there are many more companies listed on these sites than those that drop cookies via our website): - Your Online Choices [http://www.youronlinechoices.com/](http://www.youronlinechoices.com/) - Network Advertising Initiative [http://www.networkadvertising.org/](http://www.networkadvertising.org/) - Digital Advertising Alliance [http://www.aboutads.info/consumers/](http://www.aboutads.info/consumers/) - Your browser settings may also allow you to transmit a “Do Not Track” signal when you visit various websites. Like many websites, our website is not designed to respond to “Do Not Track” signals received from browsers. To learn more about “Do Not Track” signals, you can visit [http://www.allaboutdnt.com/.](http://www.allaboutdnt.com/) **8. VISITOR GENERATED CONTENT** The Connections may also share, refer to, or host content created and uploaded by visitors to the dbt Community Slack or the website, which visitors may elect to engage with. Through your participation, you may submit content (“**Visitor-Generated Content**” or “**VGC**”). We or others may store, display, reproduce, publish, or otherwise use VGC, and may or may not attribute it to you. Others may also have access to VGC and may have the ability to share it with third parties. If you choose to submit VGC to any Social Feature or public forum such as the website or a conference, your VGC will be considered “public” and will be accessible by anyone, including dbt Labs. Please note that we do not control who will have access to information that you make available to others, and cannot ensure that parties who access to such information will keep it secure or respect your privacy. We are not responsible for the privacy or security of any information you make publicly available or what others do with information shared on such platforms. We are not responsible for the accuracy, use or misuse of any VGC that you disclose or receive from third parties through the forums or email lists. **9. SOCIAL FEATURES** The dbt Community Slack forum permits chats with other data practitioners and lets you ask questions about analytics engineering, and certain features of the website permit you to initiate interactions between the website and third-party services or platforms, such as social networks (“**Social Features**”). Social Features may include features that allow you to click and access our pages on certain third-party platforms, such as Facebook, LinkedIn, and Twitter, and from there to “like” or “share” our content on those platforms. Use of Social Features may entail a third party’s collection and/or use of your information. If you use Social Features or similar third-party services, information you post or otherwise make accessible may be publicly displayed by the third-party service you are using. Both dbt Labs and the third party may have access to information about you and your use of both the website and the third-party service. For more information on third-party websites, services, and platforms, see the following Section. **10. LINKS TO THIRD PARTY SITES** Our website may, from time to time, contain links to and from third party websites, including those of other Visitors, our partner networks, advertisers, partner merchants, news publications, retailers and affiliates. If you follow a link to any of these websites, please note that these websites have their own privacy policies and that we expressly disclaim any responsibility or liability for their policies. Our inclusion of such links does not, by itself, imply any endorsement of the content on or actions of such platforms or of their owners or operators except as disclosed on the website. Please check the individual policies before you submit any information to those websites. Any information submitted by you directly to these third parties is subject to that third party’s privacy policy. **11. NOTICE TO YOU OF CHANGES TO THIS POLICY** We may update this privacy policy from time to time and so you should review this page periodically. When we change this privacy policy in a material way, we will update the “last modified” date at the end of this privacy policy. Changes to this privacy policy are effective when they are posted on this page, or such later date as may be specified in the updated privacy policy. IF YOU DO NOT AGREE TO ANY UPDATES TO THIS PRIVACY POLICY PLEASE DO NOT ACCESS OR CONTINUE TO USE THE CONNECTIONS. **12. CONTACTING US** Questions, comments and requests regarding this privacy policy are welcome and should be sent to [privacy@dbtlabs.com](mailto:privacy@fishtownanalytics.com). Further information is available from the dbt Labs Manager, Security Compliance (dbt Labs data protection and privacy officer) at privacy@dbtlabs.com. _Last Revised: This privacy policy was last modified on June 11, 2025._ ## ANNEX 1 - PERSONAL INFORMATION WE COLLECT ## ANNEX 2 - PERSONAL INFORMATION COLLECTED AUTOMATICALLY ## ANNEX 3 - COOKIES ### Cookie List A cookie is a small piece of data (text file) that a website – when visited by a user – asks your browser to store on your device in order to remember information about you, such as your language preference or login information. Those cookies are set by us and called first-party cookies. We also use third-party cookies – which are cookies from a domain different than the domain of the website you are visiting – for our advertising and marketing efforts. More specifically, we use cookies and other tracking technologies for the following purposes: #### Strictly Necessary Cookies Strictly necessary cookies are necessary for the site to function properly and cannot be switched off in our systems. These cookies are usually only set in response to actions made by you that amount to a request for services, such as setting your privacy preferences, logging in, or filling in forms. You can set your browser to block or alert you about these cookies, but blocking these cookies will prevent the site from functioning properly. These cookies typically do not store personal data. --- --- title: "Community - About" description: "Connect with over 100,000 data professionals worldwide. Share knowledge, attend events, and contribute to the future of analytics with dbt." url: "https://www.getdbt.com/community" --- # The future of data is being built together. The dbt Community is a place where data professionals of any skill level can ask questions, debate ideas, and push each other forward. [Join the Community](https://www.getdbt.com/community/join-the-community) | [See upcoming events](https://www.getdbt.com/events) *** *Never have to work alone* ## A global hub for collaborative learning. From meetups and memes to open-source packages and deep technical discussions, the dbt Community is where the world's sharpest data thinkers grow their craft and shape the future of analytics. dbt active members Slack messages sent daily open-source packages Community meetups *** ## Join the dbt community today. Connect, grow, and learn with the most engaged analytics community in data. [Sign up now](https://www.getdbt.com/community/join-the-community) | [Explore Discourse](https://discourse.getdbt.com) *** ## The dbt Community—IRL. From New York to Lagos to Berlin, our global meetup groups share knowledge, stories, and good times. *** *Open-source tooling* ## Contribute to the tools you already use From dbt Core to adapters and packages, the dbt ecosystem thrives because people give back. Level up your skills while helping thousands of others with your contribution. ### dbt-labs/dbt_utils Additional tests and utility macros that make it easier to generate complex SQL [View package](https://hub.getdbt.com/dbt-labs/dbt_utils/latest/) ### calogica/dbt_expectations A SQL port of the great_expectations projects [View package](https://hub.getdbt.com/calogica/dbt_expectations/latest/) ### brooklyn-data/dbt_artifacts A package for modeling dbt invocation metadata [View package](https://hub.getdbt.com/brooklyn-data/dbt_artifacts/latest/) *** *Something for everyone* ## There's a place for you here. There are so many ways to participate that fit your preferred style, whether that's writing code, answering questions, or even just making memes. ### Join Slack Ask questions, get answers, and meet people who speak your data language [Join dbt Community Slack](https://www.getdbt.com/community/join-the-community) ### Submit a PR Fix a bug, add a feature, or improve docs for thousands of users [Submit a pull request](https://docs.getdbt.com/community/contribute) ### Attend or host a meetup Join the conversation locally—or start your own wherever you are [See upcoming meetups](https://www.getdbt.com/events) ### Subscribe to the newsletter Get fresh community ideas, job posts, and tools delivered weekly [Subscribe today](https://www.getdbt.com/community/join-the-community) ### Help someone on Discourse Help someone solve a real problem—and build your reputation doing it [Open Discourse](https://discourse.getdbt.com/) ### Post to #memes Because the dbt Community takes its SQL seriously, but not itself [Share a meme](https://getdbt.slack.com/archives/C0VLNUUTZ) *** *See you soon* ## Join the dbt Community today. Meet others who get what you do, share what you know, and grow alongside the post passionate data professionals in the world. [Sign up now](https://www.getdbt.com/community/join-the-community) --- --- title: "dbt Meetup Organizer guide" url: "https://www.getdbt.com/community/dbt-meetups/organizer-guide" --- # dbt Meetup Organizer Guide Once you’ve launched your local dbt Meetup, here’s everything you need to keep it running—from finding speakers to staying connected with dbt Labs in the private meetup-organizer Slack channel. [View all resources and templates](#resource-hub) *** ## Event Submission & Swag **Submit the **[Meetup Submission Form](https://forms.gle/tnfRSNdYyq2ek5v77)** at least 3 weeks before your meetup** (4 weeks if you're requesting swag), and **always before posting the event on [Meetup.com](http://Meetup.com)**. One submission is required per meetup. You don't need finalized details — this form is just to signal that a meetup is coming. At minimum, include the expected month, though a tentative date is preferred. _ **Note:** This form does not replace creating the event on [Meetup.com](https://www.getdbt.com/) — see the following section for details._ [View all resources and templates](#resource-hub) *** ## Meetup.com Landing page **Your landing page sets the tone for your event. Publish early and publish complete. A clear, fully detailed page drives sign-ups and builds trust.** - **Publish early:** Post your landing page at least 3 weeks before the event. Please be sure to confirm your agenda and speakers before publishing (no TBD agenda items, please.) - **Add full speaker details:** Include name, title, company, and talk topic for each speaker. - **Follow the template:** Use the most recent [official landing page format](https://docs.google.com/document/d/1L7lyJrwdbgIzBfodOiK3xjnPWQN3deexxARtxMsJKdE/edit?tab=t.0). The template is updated periodically to reflect brand and program requirements. - **Include required legal copy:** Add: “To attend, please read the Health and Safety Policy and Terms of Participation: https://www.getdbt.com/legal/health-and-safety-policy” - **Attendee confirmation:** In “Ask Members a Question,” paste: “I agree to read and abide by the Health and Safety Policy and Terms of Participation. Please type ‘Yes’ to confirm.” - **Plan for no-shows:** Expect 50–60% attendance. For a 50-seat venue, cap RSVPs at 85–100. - **Set required registration fields:** Require "First + Last Name", "Current Role", and "Organization". Other fields are optional. 💬 **Still need help?** Reach out in the private meetup-organizers-team Slack channel. [View all resources and templates](#resource-hub) *** ## Venue & Catering Choose a venue that’s comfortable, welcoming—and not a competitor. - **No competitor-hosted meetups**. Not sure? Ask the Community team at [meetup@dbtlabs.com](mailto: meetup@dbtlabs.com) - **Offices are great.** Yours, a speaker’s, or an attendee’s workplace often works best. - **Breweries and bars are great for casual networking or happy hours.** But for talks or presentations, choose a quieter venue where people can hear and stay engaged. 🍕 **Keep food simple** Pizza’s great! Just be sure to include vegetarian, vegan, and gluten-free options. **Note: **Check with the Community team to confirm your meetup location's food and beverage budget. Do not use the budget for venue expenses unless the Community team approves. [View all resources and templates](#resource-hub) *** ## Design Keep your visuals aligned with dbt’s brand—consistent design builds trust and makes your event feel official. - **Use the [dbt logo](https://www.getdbt.com/brand-guidelines)** (not dbt Labs) - **Follow the templates** for [Meetup.com images](https://docs.google.com/presentation/d/1VqV6C5v0_kvWvhS3EtlWjdvZBRHlXj6bcFfc8U1Ii_g/edit?usp=sharing) and [host slides](https://docs.google.com/presentation/d/12Ieg_lSfT9F8__KtEExUHTmsaFR-FJD9UjCQykoHYcc/edit?usp=sharing) - **Don’t edit colors or themes**, even if others do - **Speakers can use their own slides**, but your intro/closing slides should use the official deck - **Always make a copy of the latest version** 1 week before your event to get any updates - **For the survey slide**, email the team at [meetup@dbtlabs.com](mailto: meetup@dbtlabs.com) for the reusable QR code [View all resources and templates](#resource-hub) *** ## Content Guidelines Keep it educational, not promotional. Talks should center on real-world problems, with dbt playing a meaningful role in the solution. - You can **cover topics like analytics engineering, team structure, testing, or modeling**—just make sure the story includes dbt. - Stories using both **dbt and dbt Core** are welcome and encouraged. - Vendor practitioners can speak _about their customers_ from a **practitioner’s POV**. 🚫 Avoid sales pitches, product demos, or founder spotlights. [View all resources and templates](#resource-hub) *** ## Meetup Promotion Get the word out early and often—strong promotion helps drive attendance and build your local data community. - **Share in Slack**: Post in #local-[your city] ([see optional template](https://docs.google.com/document/d/1gC5LawScSMbwgbEcHDHpcvkiC-Dg0Rw--14_KdM-nTY/edit?tab=t.0)) - **Leverage your speakers**: Ask them to promote the event to their networks - **Promote, promote, promote**: Share your event on LinkedIn and anywhere else you engage with the data community - **Use the “Announce” button**: After publishing your event, click the red button on Meetup to email all group members—time it for maximum visibility - **Create a visual**: Use the [promo deck template](https://docs.google.com/presentation/d/1VqV6C5v0_kvWvhS3EtlWjdvZBRHlXj6bcFfc8U1Ii_g/edit?usp=sharing) to design graphics for Meetup.com and social media - **Take photos**: Good photos help promote future events. Share them in Slack and upload to your event page! [View all resources and templates](#resource-hub) *** ## After the event Close strong and keep the connections going. After each event, **create a new folder in your chapter's Google Drive titled with the meetup date, and upload all photos and videos.** If you don't have access to the Drive, send an email to [meetup@dbtlabs.com](mailto:meetup@dbtlabs.com) *** ### Follow up to keep the energy alive A little post-event follow-up helps build community and show appreciation. - Message your group on Meetup (template available). - Post in #local-[your city] with: - Thanks to speakers + attendees - Quick recap - Slides, links, or dbt Summit info - Event photos - Upload some key photos to your Meetup event page ![Floripa dbt Meetup, March 2026](https://cdn.sanity.io/images/wl0ndo6t/main/c11a77a0cbbb89752117a13a92694552725fcbca-2048x1152.jpg) *** ### Reimbursements **_Invoices must be submitted within 30 days from the event date._** We’re able to support some meetup costs—but budget is limited and handled case by case. (If you work at dbt Labs, message the Community Manager for a different process.) - **Covered expenses**: Food, drinks, and paper goods - **Sometimes covered:** Venue - please discuss with the Community team if you need support securing a venue **prior to booking** - **Not covered**: A/V gear or speaker travel (flights, hotels, etc.) **To ensure no delays with reimbursement:** **Before your event**: Send the Community meetup team ([meetup@dbtlabs.com](mailto: meetup@dbtlabs.com)) the name and email of the person at your company who will: - Create a [Coupa](https://www.fivetran.com/vendors) account - Add banking details - Upload invoices **After your event**: - Create an invoice [following this template](https://docs.google.com/document/d/1VkXyCxXmmaBMOdWMi8FJnfC9dCvG9od67tktU0FsZN4/edit?usp=sharing) - Add your PO number (updated yearly around February) - Include receipts (screenshots or photos are fine) - Download as PDF and upload to [Coupa](https://www.fivetran.com/vendors) **_Payment is processed within 30 days of receiving the invoice._** *** ## Suggestions Tips and tricks to help make your dbt Meetup memorable, inclusive, and community-first. Keep an eye on the #meetup-organizers-team Slack channel to stay up to date on new resources, event tips, and updates. ### Keep the vibe community-first Avoid pop-up banners or anything too branded. Focus on learning, sharing, and connection. ### Let attendees know what to expect Include topic descriptions alongside speaker names and titles to set expectations and draw interest. ### Check in before showtime Use the Meetup page to send a reminder and get a more accurate headcount—helps with food, space, and waitlist planning. ### Spotlight real stories The best talks come from practitioners sharing how they solved real problems with dbt. ### Make intros easy (and fun) Bring name tags, chat prompts, or even a community game like Bingo to break the ice and spark real conversations. ### Capture the moment Take photos (with consent), not just of speakers but of the whole room—community matters. ### Test your tech ahead of time Make sure slides, mics, and any screen sharing work before guests arrive—it saves stress and awkward silences. ### Find your next speaker Use the networking hour to discover potential speakers—many don’t realize their work is already talk-worthy. ### Encourage inclusive voices Actively invite women and underrepresented folks to speak—it makes for richer, more relevant discussions. *** 💬 **Still need help? **Reach out in the private meetup-organizers-team Slack channel to connect with others hosting meetups, ask questions, and stay in the loop with the latest updates. *** ## Resource Hub Save time with ready-made assets for every step of your event. ### Speaker & Promotion toolkit [Get dbt Meetup toolkit](https://docs.google.com/presentation/d/1VqV6C5v0_kvWvhS3EtlWjdvZBRHlXj6bcFfc8U1Ii_g/edit?usp=sharing) ### Presentation slides [Download presentation template](https://docs.google.com/presentation/d/12Ieg_lSfT9F8__KtEExUHTmsaFR-FJD9UjCQykoHYcc/edit?usp=sharing) ### Meetup page template [Download Meetup description template](https://docs.google.com/document/d/1L7lyJrwdbgIzBfodOiK3xjnPWQN3deexxARtxMsJKdE/edit?tab=t.0) ### Event announcement toolkit [View announcement toolkit](https://docs.google.com/document/d/1nIa4pban0WEunn1P2Ope1H6UwmJh0nXCy-exctBXa7Y/edit?usp=sharing) ### dbt Meetup Bingo [Download Bingo template](https://docs.google.com/document/d/1zuQI0UgLWo6SA2WEY12TuLgdWTjDY6mAsCadE33PosI/edit?tab=t.0) ### Post-event Meetup.com 'Thank You' + Feedback template [Post-event Meetup.com 'Thank You' + Feedback template](https://docs.google.com/document/d/1rVSUC8R8gxAXRhHZVWVf3Q-WdfN-ie1NgTQ6L0KlG1Y/edit?usp=sharing) ### Post-event Slack template [View Slack template](https://docs.google.com/document/d/1ysWxXrDLCVjmDF3mI8GIuK2ZEix-dq_aWi34Burk5xg/edit?usp=sharing) ### Reimbursement template [Get invoice template](https://docs.google.com/document/d/1Mbw75sOF1fzKWIYkeiDv71row8tI-HJlejcnOxaWCMY/edit?tab=t.0) ### dbt Logos / Branding [View dbt Meetup logos](https://www.getdbt.com/brand-guidelines) --- --- title: "How to host a dbt Meetup" url: "https://www.getdbt.com/community/dbt-meetups/overview" --- # Your city. Your data community. Your dbt Meetup. Use this guide to create a welcoming space for local data folks to connect, share, and learn. [dbt Community Meetup](https://www.meetup.com/pro/dbt/) | [dbt Meetup Organizer Guide](https://www.getdbt.com/community/dbt-meetups/organizer-guide) *** ## What is a dbt meetup? Meetups are locally organized, in-person events for folks working with data and building with dbt. Whether you’re deep in the weeds of your DAG or managing a growing team, these gatherings are for real conversations and connections. ![Austin, TX dbt Meetup, April 2025](https://cdn.sanity.io/images/wl0ndo6t/main/4bc4d057137744c679e5874b5779399ab735292a-1600x1067.jpg) ### Local, consistent, community-led Each meetup happens in a specific city, **6–10 times per year**. They’re led by local champions who commit to running a consistent program for at least 12 months. ### Run by data people, for data people Meetups are **independently run** by local champions — either individuals or small teams — who take the lead on topics, speakers, venues, and promotion. dbt Labs offers support to help you get started, but **organizers drive the program end-to-end.** ### Hosted on the dbt Meetup network All dbt Meetups live on our official [dbt Meetup network](https://www.meetup.com/pro/dbt/) — where event pages are hosted, RSVPs are collected, and your local community gets discovered. ### Supported by dbt Labs You’re not on your own. Our Community Team helps you get started, provides event resources, and makes sure your meetup aligns with the [dbt Community Code of Conduct](https://www.getdbt.com/community/code-of-conduct/) and [vendor guidelines](https://docs.getdbt.com/community/resources/community-rules-of-the-road#vendor-expectations). *** ## Who runs dbt Meetups? You do! We’re looking for individual contributors, small teams, or anyone passionate about dbt and data to organize meetups in their city. Organizers take the lead on: - Finding speakers and venues - Promoting the events - Running the show You’ll run things autonomously, with light-touch enablement from dbt Labs—and ongoing support and updates in the `#meetup-organizers` Slack channel. [dbt Meetup Organizer Guide](https://www.getdbt.com/community/dbt-meetups/organizer-guide) *** *Community-powered, dbt-supported* ## You lead. We’ve got your back. You’re running the show, but we’re here to help with tools, templates, and just enough guidance to keep things smooth. ### Launch your local group We’ll set up your city’s dbt Meetup page and help you get started. [dbt Meetup network](https://www.meetup.com/pro/dbt/) ### Stay connected in Slack We’ll add you to #meetup-organizers and create your #local-[city] channel to keep you in the loop with updates and resources. [Maintaining a local Slack channel](https://docs.getdbt.com/community/resources/maintaining-a-channel) ### Boost your event’s visibility We’ll share your event on LinkedIn, getdbt.com/events, and docs.getdbt.com. [dbt Community Events ](https://www.getdbt.com/events) ### Share our ready-to-go templates We’ll provide templates for slides, social images, and RSVP surveys to make setup simple. [dbt Meetup resources and templates](https://www.getdbt.com/community/dbt-meetups/organizer-guide#resource-hub) ### Get occasional speaker support You’ll find your own speakers, but we may suggest or join a talk now and then—no guarantees. [Learn more](https://www.getdbt.com/community/dbt-meetups/organizer-guide#suggestions) ### Request swag and light budget Need stickers or support? Let us know with lead time—requests are limited and case by case. [Learn more](https://www.getdbt.com/community/dbt-meetups/organizer-guide#swag) *** *Join 100,000+ data professionals* ## Great data work never happens alone. The dbt Community connects you with thousands of data practitioners, leaders, and learners—all solving real problems, sharing best practices, and growing their careers together. - - - [Join the Community](https://www.getdbt.com/community/join-the-community) | [Explore Community resources](https://www.getdbt.com/community) --- --- title: "Join the Community" description: "Join the dbt Community — a global network of data professionals. Access resources, events, and collaborations to advance your analytics journey." url: "https://www.getdbt.com/community/join-the-community" --- # Join The Community Sign up to join [the dbt Community](https://www.getdbt.com/community) — a thriving hub for data professionals who know and love dbt. Join a collaborative, supportive network where you can connect, grow your skills, and contribute to the evolving field of data transformation. No matter where you are on your data journey, the dbt Community offers the resources and connections to help you succeed. ### Why join the dbt Community? - **Learn and get support**: Access tutorials, guides, and forums designed to help you master dbt and expand your data skills. - **Network with your peers**: Connect with a global community of data enthusiasts, from beginners to expert analytics engineers. - **Advance your skills**: Take part in workshops, join events, and engage in real-world projects to deepen your dbt expertise. - **Contribute and collaborate**: Share your knowledge, collaborate on open-source projects, and play a part in shaping the dbt ecosystem. - **Stay informed**: Get insights on the latest trends in data transformation, analytics engineering, and the dbt tool. Become part of a community that's shaping the future of data. Join us today and take your place in the dbt Community! --- --- title: "dbt Community rules and expectations" description: "Understand the principles for participating in the dbt Community. Learn about respectful engagement, messaging etiquette, and vendor expectations." url: "https://www.getdbt.com/community/rules-and-expectations" --- # Community rules and expectations *** People genuinely love this community. It's filled with smart, kind, and helpful people who share our commitment to elevating the analytics profession. We are committed to maintaining the spirit of this community, and have written these rules alongside its members to help everyone understand how to best participate. We appreciate your support in continuing to build a community we're all proud of. ## Expectations for all members ### Rule 1: Be respectful We want everyone in this community to have a fulfilling and positive experience. Therefore, this first rule is serious and straightforward; we simply will not tolerate disrespectful behavior of any kind. Everyone interacting on a dbt platform – including Slack, the forum, codebase, issue trackers, and mailing lists – is expected to follow the [Community Code of Conduct](https://docs.getdbt.com/community/resources/code-of-conduct). If you are unable to abide by the code of conduct set forth here, we encourage you not to participate in the community. ### Rule 2: Keep it in public spaces Unless you have someone's express permission to contact them directly, do not directly message other community members, whether on a dbt Community platform or other spaces like LinkedIn. ### Rule 3: Follow messaging etiquette In short: put effort into your question, use threads, post in the right channel, and do not seek extra attention by tagging individuals or double-posting. For more information, see our [guide on getting help](https://docs.getdbt.com/community/resources/getting-help). ### Rule 4: Do not solicit community members This community is built for data practitioners to discuss the work that they do, the ideas that they have, and the things that they are learning. It is decidedly not intended to be lead generation for vendors or recruiters. Vendors and recruiters are subject to additional rules to ensure this space remains welcoming to everyone. These requirements are detailed below and are enforced vigorously. ## Vendor expectations ### Who is a vendor? Vendors are generally individuals belonging to companies that are creating products or services primarily targeted at data professionals, but this title also includes recruiters, investors, open source maintainers (with or without a paid offering), consultants and freelancers. If in doubt, err on the side of caution. ### Rule 1: Identify yourself Include your company in your display name, e.g. "Alice (DataCo)". When joining a discussion about your product (after the waiting period below), be sure to note your business interests. ### Rule 2: Let others speak first If a community member asks a question about your product directly, or mentions that they have a problem that your product could help with, wait 1 business day before responding to allow other members to share their experiences and recommendations. ### Rule 3: Keep promotional content to specified spaces As a space for professional practice, the dbt Community is primarily a non-commercial space. However, as a service to community members who want to be able to keep up to date with the data industry, there are several areas available on the Community Slack for vendors to share promotional material: - #vendor-content - #events - Your product's #tools-* channel - Recruiters may also post in #jobs/#jobs-eu but may not solicit applications in DMs. The definition of "vendor content" can be blurry at the edges, and we defer to members' instincts in these scenarios. As a rule, if something is hosted on a site controlled by that company or its employees (including platforms like Substack and Medium), or contains a CTA such as signing up for a mailing list or trial account, it will likely be considered promotional. ## One more tip: Be yourself Speak in your own voice, and join in any or all of the conversations that interest you. Share your expertise as a data professional. Make a meme if you're so inclined. Get in a (friendly) debate. You are not limited to only your company's products and services, and making yourself known as a familiar face outside of commercial contexts is one of the most effective ways of building trust with the community. Put another way, [create more value than you capture](https://docs.getdbt.com/community/resources/code-of-conduct#create-more-value-than-you-capture). Because unaffiliated community members are able to share links in any channel, the most effective way to have your work reach a wider audience is to create things that are genuinely useful to the community. Already a member? Sign in to [Slack](https://getdbt.slack.com/) or [the Forum](https://discourse.getdbt.com/login). --- --- title: "Book a Demo" description: "Talk with our team to learn how dbt can drive value for your business. Explore a tailored solution for your data transformation needs." url: "https://www.getdbt.com/contact" --- # Talk to a dbt expert Get your questions answered directly by a dbt expert. You'll get a live demo on how dbt works, why it's an industry standard, and what it can do for your team. - Develop faster - Build data quality and trust - Unite your team **Trusted by the best in data** *** ### Create a dbt account Start building trusted data products, faster with a free dbt account. [Create an account](https://www.getdbt.com/signup) ### Find the right plan Explore pricing options and find the best fit for you, your team, and your needs. [Explore pricing](https://www.getdbt.com/pricing) ### Contact support Already a dbt customer? Get in touch with support for additional help. [Get in touch](https://docs.getdbt.com/docs/dbt-cloud/cloud-dbt-cloud-support) *** *Why teams trust dbt* ## Trusted globally. Proven at scale. ### 80,000+ teams using dbt dbt powers trusted analytics workflows and data at scale for the world's largest companies ### Top-rated on G2 Recognized in Gartner's DataOps Market Guide 2024 ### Built with leading partners ### 100K+ Community members Join the largest open data community sharing best practices and building better data products --- --- title: "Data Platforms - BigQuery" description: "Build scalable, reliable data pipelines by combining dbt’s transformation capabilities with BigQuery’s powerful analytics engine." url: "https://www.getdbt.com/data-platforms/bigquery" --- # Simplify your data transformation. Build, manage, and optimize data pipelines with efficiency and precision–with dbt and BigQuery. [Book your demo](https://www.getdbt.com/contact) | [Explore dbt on Google Cloud Marketplace](https://console.cloud.google.com/marketplace/browse?filter=partner:dbt%20Labs) *** *dbt + BigQuery* ## Transform data at scale with dbt and BigQuery With dbt users can create and manage scalable data workflows that execute efficiently on BigQuery’s compute resources. ### Scale and save time dbt and BigQuery enable teams to automate complex data transformations efficiently, handling even large volumes of data with ease. [Learn how Bluecore scaled their warehouse](https://www.getdbt.com/resources/coalesce-on-demand/scaling-dbt-and-bigquery-to-infinity-and-beyond-from-coalesce-2023) ### Improve data quality and governance Built-in data testing, automated documentation, and data lineage ensure that transformed data in BigQuery is accurate, reliable, and easy to audit. [Learn how DISH improved their data quality](https://www.getdbt.com/case-studies/dish-digital-solutions) ### Streamline collaboration and development With version control, job scheduling, and CI/CD workflows, teams can work together on data models, track changes, and deploy updates seamlessly–creating a more agile and efficient data workflow. [Build the case for dbt today](https://www.getdbt.com/resources/making-the-case-for-dbt-cloud) *** ## Launch dbt on BigQuery in just a few steps Get up and running in minutes with our step-by-step guide. Connect your data, build models, and start transforming with ease. - No complex setup—just follow a few simple steps - Automate and scale your data transformations effortlessly - Leverage built-in testing and documentation for better data quality [Read the guide](https://docs.getdbt.com/guides/bigquery) | [Enroll in the setup course](https://learn.getdbt.com/courses/dbt-cloud-and-bigquery-for-admins) *** ## See what dbt can do with BigQuery. Explore how teams use dbt to move faster, build trust, and scale with confidence. [Explore dbt](https://www.getdbt.com/product/dbt) *** ## Data teams trust dbt + BigQuery Leading organizations use dbt and BigQuery to reduce the cost of producing insights and improve trust in data. ### Bilt Rewards saves 80% in analytics costs with the dbt Semantic Layer > “By centralizing our entity relationships in the dbt Semantic Layer, where all of our data transformations already live, we could easily create visualizations in our B2B product. We delivered an improved data experience for our B2B partners by eliminating a step in our process, decreasing our data costs by 80%, and increasing reliability and trust.” [Read more](https://www.getdbt.com/case-studies/bilt-rewards) ### DISH Digital Solutions scales data operations with dbt Cloud > “Our process is totally different than it was before dbt Cloud, where people worked in silos without visibility on who was doing what. The new workflow increased our data quality while improving transparency and collaboration.” [Read more](https://www.getdbt.com/case-studies/dish-digital-solutions) ### Rocket Money modernizes financial reporting with dbt Cloud > "Having this automated Quote-to-Cash system run in dbt with our test suite allows us to confidently and quickly close our books each month." [Read more](https://www.getdbt.com/case-studies/rocket-money) *** *Additional resources* ## Go further with dbt + BigQuery. Learn about how dbt supports AI use-cases from architecture to implementation. ### What's new from Google Cloud Next 25 ### dbt Developer Day ### Accelerating dbt with SDF *** *Why teams trust dbt* ## Trusted globally. Proven at scale. ### 80,000+ teams using dbt dbt powers trusted analytics workflows and data at scale for the world's largest companies ### Google Cloud Partner of the Year 2026 For Data & Analytics - Pipelines & Governance ### Built with leading partners ### 100K+ Community members Join the largest open data community sharing best practices and building better data products *** ## Learn how to optimize your Google BigQuery stack with dbt today. Schedule a demo to see how dbt enhances your BigQuery investment, accelerates workflows, and delivers better analytics outcomes. [Book your demo](https://www.getdbt.com/contact) | [Quick start: dbt + BigQuery](https://docs.getdbt.com/guides/bigquery?step=1) --- --- title: "Data Platform - Databricks" description: "Transform and scale analytics on Databricks using dbt. Build trusted, governed data pipelines with speed and confidence." url: "https://www.getdbt.com/data-platforms/databricks" --- # Quickly turn raw data into valuable insights. Streamline data transformation and AI/BI workflows on the Lakehouse, enabling teams to build, test, and deploy data models efficiently with dbt and Databricks. [Book your demo](https://www.getdbt.com/contact) | [Connect dbt and Databricks](https://docs.getdbt.com/guides/databricks?step=1) *** *dbt + Databricks* ## Enhance the power of Databricks with dbt Empower more teams to build, collaborate, and scale AI-driven data products by connecting dbt with Databricks. Simplify workflows, enhance collaboration, and make data accessible across your organization—all while reducing costs and increasing efficiency. ### Succeed with AI Enable any data team to develop AI applications on your data without sacrificing data privacy or control [Read the Databricks Data + AI Summit recap](https://www.getdbt.com/blog/the-best-data-ai-summit-yet-is-in-the-books) ### Democratize insights Empower everyone in your organization to discover insights from your data using natural language with dbt and Databrick's native AI/BI [Learn how Explorium enables data teams](https://www.databricks.com/customers/explorium) ### Drive down the cost of insights Evaluate your models before sending to the warehouse, increase reuse of data assets and speed the time to deploy with dbt on Databricks [Read how Kaltura cut spend with dbt](https://www.databricks.com/customers/kaltura) *** ## dbt + Databricks go hand in hand. Deploying dbt with Databricks transforms data, integrates with Unity Catalog and provides metadata to AI & ML workflows. [Use the quick start guide to get started.](https://docs.getdbt.com/guides/databricks?step=1) *** ## See what dbt can do with Databricks. Explore how teams use dbt to move faster, build trust, and scale with confidence. [Explore dbt](https://www.getdbt.com/product/dbt) *** ## Data teams trust dbt + Databricks Leading organizations use dbt and Databricks to streamline data transformation ### Retool builds scalable, self-serve analytics with dbt Cloud and Databricks > “dbt on Databricks allowed Retool to get value out of data really quickly. We were generating large quantities of product usage data and we needed insights without having to hire a data team first.” [Read more](https://www.getdbt.com/case-studies/retool) ### Aktify democratizes data access with Databricks Lakehouse Platform and dbt > “Databricks Lakehouse Platform and dbt have eliminated the manual tasks and errors from our data transformations. We’ve been able to stand up new solutions for internal clients in half a day compared to 3-5 days previously.” [Read more](https://www.getdbt.com/case-studies/aktify) *** *Additional resources* ## Go further with dbt + Databricks. Learn about how dbt supports AI use-cases from architecture to implementation. ### dbt + Databricks quick start Ready to build? Get started with our Databricks quick start tutorial and detailed documentation. ### Create a free account Sign up for free solo developer account or try dbt with your team for a 14-day trial—no credit card required. ### Book an expert-led demo Learn how dbt and Databricks can help your team and get custom insights from a dbt expert. *** ## Learn how to optimize your Databricks stack with dbt today. Schedule a demo to see how dbt enhances your Databricks investment, accelerates workflows, and delivers better analytics outcomes. [Book your demo](https://www.getdbt.com/contact) | [Quick start: dbt + Databricks](https://docs.getdbt.com/guides/databricks?step=1) --- --- title: "Data Platforms - Fivetran" description: "Accelerate analytics by automating ELT workflows. Combine Fivetran’s data loading with dbt’s transformations for efficient, reliable pipelines." url: "https://www.getdbt.com/data-platforms/fivetran" --- # Manage every stage of data integration. Simplify data pipeline setup and maintenance, helping data teams move faster and work on the highest priority data tasks–with dbt and Fivetran. [Book your demo](https://www.getdbt.com/contact) | [Guide to dbt + Fivetran](https://www.getdbt.com/resources/how-fivetran-and-dbt-help-with-elt) *** *dbt + Fivetran* ## Unlock the power of dbt and Fivetran for a more scalable and efficient data stack More than 1,000 customers rely on dbt and Fivetran to automate and accelerate their data pipelines and reduce technical overhead. Set dbt jobs to automatically run as soon as Fivetran loads new data into the warehouse. Minimize latency, deliver insights faster, and optimize compute jobs by running jobs with the freshest data available. ### Reduce complexity Avoid complex ETL code and simplify team workflows by integrating Fivetran’s data loading with dbt's transformations, lineage and semantics. [Read the integration announcement](https://www.getdbt.com/blog/announcing-the-fivetran-dbt-cloud-integration) ### Save hours Save time and optimize compute resources by running data transformations inside your warehouse. [Learn how AXS saved valuable time](https://www.getdbt.com/case-studies/axs) ### Improve collaboration Accelerate time to business insights by making it easier for data engineers and analysts to work together quickly with the reusability and discoverability of dbt transformations. [Read more about the ELT paradigm](https://www.getdbt.com/product/elt-migration) *** ## Watch how easy ELT can be with Fivetran and dbt. Discover how Fivetran and dbt work together to streamline your data pipeline. With a fully managed integration, you can automate data movement, transformations, and governance—no complex setup required. Watch now and simplify your path to insights. [Watch video](https://fast.wistia.net/embed/iframe/2cl8r90fu8) *** ## See what dbt can do with Fivetran. Explore how teams use dbt to move faster, build trust, and scale with confidence. [Explore dbt](https://www.getdbt.com/product/dbt) *** *Additional resources* ## Go further with dbt + Fivetran. Learn about how dbt supports AI use-cases from architecture to implementation. ### dbt + Fivetran for ELT ### dbt Developer Day ### Accelerating dbt with SDF *** ## Learn how to optimize your workflow with Fivetran and dbt today. Schedule a demo to see how dbt enhances your Fivetran investment, accelerates workflows, and delivers better analytics outcomes. [Book your demo](https://www.getdbt.com/contact) | [Fivetran + dbt Integration](https://www.getdbt.com/blog/announcing-the-fivetran-dbt-cloud-integration) --- --- title: "Data Platforms - Microsoft Fabric" description: "Integrate dbt with Microsoft Fabric to build scalable, secure data pipelines. Streamline transformations and enhance analytics workflows." url: "https://www.getdbt.com/data-platforms/microsoft-fabric" --- # The data control plane for Microsoft Fabric. Connect to Azure-based data warehouses to develop, test, and run data transformations in SQL with dbt Cloud and Microsoft Fabric. [Book your demo](https://www.getdbt.com/contact) | [Get started with dbt and Microsoft Fabric](https://docs.getdbt.com/guides/microsoft-fabric?step=1) *** *dbt + Microsoft* ## Seamless data transformations with dbt and Microsoft dbt natively supports Microsoft Fabric and Azure Synapse Analytics, enabling data teams to build and scale modern data workflows with built-in security, governance, and enterprise-grade performance. Transform, orchestrate, and optimize your data—all in one place. ### Unify data transformations
 Transform raw data into analytics-ready datasets within Microsoft Fabric—eliminating data movement, reducing latency, and streamlining workflows. [Manage data complexity at scale](https://www.getdbt.com/resources/manage-data-complexity-at-scale-ebook) ### End-to-end orchestration Schedule, automate, and sync data transformations within broader pipelines to keep data up-to-date and ready for analysis. [Connect Microsoft Fabric today](https://docs.getdbt.com/docs/cloud/connect-data-platform/connect-microsoft-fabric) ### Enhance governance and security Microsoft Fabric and dbt provide data lineage, metadata, and security tools to improve visibility, quality, and trust. [Learn more about governance with dbt](https://www.getdbt.com/product/governance) *** ## Unlock the full potential of Microsoft Fabric with dbt. Seamlessly integrate dbt with Microsoft Fabric to transform, manage, and analyze data—all in one place. - Execute SQL-based transformations directly in Fabric - Eliminate data silos and reduce latency for real-time insights - Enhance governance, observability, and collaboration - Streamline workflows and improve data quality *** ## See what dbt can do with Microsoft Fabric. Explore how teams use dbt to move faster, build trust, and scale with confidence. [Explore dbt](https://www.getdbt.com/product/dbt) *** ## Data teams trust dbt + Microsoft Fabric Leading organizations use dbt and Microsoft Fabric to reduce the cost of producing insights and improve trust in data. ### Nasdaq empowers business users with dbt Cloud and a modern data stack > “Before, 9 out 10 times the sales and executive team had to wait months to receive a data point they requested. By then, the data wasn’t relevant anymore or the new business was already lost.” [Read more](https://www.getdbt.com/case-studies/nasdaq) ### Pepperstone creates data decision makers can rely on > “Trust is so important because we are the experts in data analysis. And if you have a good level of trust, your insights are more likely to be robustly discussed.” [Read more](https://www.getdbt.com/case-studies/pepperstone) ### SafetyCulture gets serious about company OKRs with dbt Cloud > “The data team knew there was a better way. We needed to invest in building the foundations to be able to operate at the right level.” [Read more](https://www.getdbt.com/case-studies/safetyculture) *** *Additional resources* ## Go further with dbt + Microsoft Fabric. ### dbt now available for Microsoft Fabric ### dbt Developer Day ### Accelerating dbt with SDF *** ## Learn how to optimize your data stack with dbt today. Schedule a demo to see how dbt enhances your Microsoft Fabric investment, accelerates workflows, and delivers better analytics outcomes. [Book your demo](https://www.getdbt.com/contact) | [Quick start: dbt + Fabric](https://docs.getdbt.com/guides/microsoft-fabric?step=1) --- --- title: "Data Platform - Redshift" description: "Transform and scale analytics on Amazon Redshift using dbt. Build trusted, governed data pipelines with speed and confidence." url: "https://www.getdbt.com/data-platforms/redshift" --- # Build actionable insights with flexibility. Transform, model, and document your data across the AWS landscape with dbt Cloud, enabling teams to build scalable, analytics-ready datasets faster than ever using Amazon Redshift and Athena. [Book your demo](https://www.getdbt.com/contact) | [Explore dbt on AWS Marketplace](https://aws.amazon.com/marketplace/pp/prodview-tjpcf42nbnhko) *** *dbt + AWS* ## Maximize your data potential with dbt + AWS Leverage dbt's seamless integration with AWS to transform, manage, and analyze your data efficiently. ### Scale with flexibility Choose the AWS services that best meet your data needs across Redshift, Athena, Glue, and SageMaker Lakehouse. Gain visibility across your AWS data landscape with cross-platform dbt Mesh. [Read about cross-platform data mesh](https://www.getdbt.com/blog/one-dbt-cross-platform-data-mesh) ### Increase collaboration Eliminate silos and bottlenecks with SQL-driven development, allowing analysts and engineers to collaborate on data transformation and modeling. [Maximize business value with dbt + AWS](https://www.getdbt.com/resources/webinars/new-in-dbt-cloud-a-four-part-series-on-maximizing-value) ### Improve trust Develop data pipelines with engineering best practices like CI/CD, version control, testing, and automatic documentation. [Connect dbt and Redshift today](https://docs.getdbt.com/guides/redshift) *** ## Scalable, AI-ready data mesh with dbt and AWS. Discover how Moderna unifies its data platforms—Redshift, Athena, and more—using dbt to build a governed, scalable data mesh. Learn how they break down silos, streamline analytics, and enable AI-driven insights with a powerful data control plane. [Watch video](https://www.youtube.com/watch?v=Vb6qSMN2AoU&t=1s) *** ## See what dbt can do with AWS. Explore how teams use dbt to move faster, build trust, and scale with confidence. [Explore dbt](https://www.getdbt.com/product/dbt) *** ## Data teams trust dbt + AWS Leading organizations use dbt and AWS to reduce the cost of producing insights and improve trust in data. ### Nasdaq empowers business users with dbt Cloud and a modern data stack > “Before, 9 out 10 times the sales and executive team had to wait months to receive a data point they requested. By then, the data wasn’t relevant anymore or the new business was already lost.” [Read more](https://www.getdbt.com/case-studies/nasdaq) ### Pepperstone creates data decision makers can rely on > “Trust is so important because we are the experts in data analysis. And if you have a good level of trust, your insights are more likely to be robustly discussed.” [Read more](https://www.getdbt.com/case-studies/pepperstone) ### SafetyCulture gets serious about company OKRs with dbt Cloud > “The data team knew there was a better way. We needed to invest in building the foundations to be able to operate at the right level.” [Read more](https://www.getdbt.com/case-studies/safetyculture) *** *Additional resources* ## Go further with dbt + AWS. Learn about how dbt supports AI use-cases from architecture to implementation. ### Review the AWS re:Invent 2024 recap ### dbt Developer Day ### Accelerating dbt with SDF *** ## Learn how to optimize your AWS stack with dbt today. Schedule a demo to see how dbt enhances your AWS investment, accelerates workflows, and delivers better analytics outcomes. [Book your demo](https://www.getdbt.com/contact) | [Quick start: dbt + AWS](https://docs.getdbt.com/guides/redshift) --- --- title: "Data Platforms - Snowflake" description: "Combine dbt with Snowflake to build trusted, scalable data pipelines. Enhance governance, reduce costs, and deliver AI-ready analytics faster." url: "https://www.getdbt.com/data-platforms/snowflake" --- # Accelerate your Snowflake analytics with dbt. Using dbt with Snowflake enables data teams to efficiently deliver trusted, scalable data faster and with reduced cost. [Book your demo](https://www.getdbt.com/contact) | [Start with dbt + Snowflake](https://app.snowflake.com/marketplace/listing/GZTYZ60LJOWGX/dbt-labs-dbt-platform) *** *dbt + Snowflake* ## Built for data teams that care about speed and trust. Snowflake delivers the performance. dbt adds structure, governance, and velocity to what your team builds on top of it. Together, they unlock a production-grade workflow to transform raw data into AI-ready inputs. The dbt Fusion engine is the future of dbt, and Snowflake dbt Projects will soon be powered by the dbt Labs Fusion engine. Get the most modern engine, right inside of Snowflake. ### Data trust = AI trust Built-in logging, alerting, and column-level lineage ensure high-quality transformations all while making the transformation metadata available to AI applications. [Watch how to boost AI reliability](https://www.getdbt.com/resources/webinars/boost-ai-reliability-with-dbt-cloud) ### Optimize cost Ensure quality code reaches production, and reduce redundant work by enabling teams to leverage existing projects [Learn how Code42 improved their ROI](https://www.getdbt.com/resources/webinars/less-maintenance-more-roi) ### Build faster, at scale Fusion is the next-generation dbt engine that's powering a more responsive developer experience, cost efficiencies, and the future of analytics [See how Fusion accelerates development](https://www.getdbt.com/product/fusion) *** ## Seamless integration with Snowflake. dbt sits directly within your Snowflake workflow, bringing advanced governance, transparent lineage, and semantic clarity to your analytics. *** ## See what dbt can do with Snowflake. Explore how teams use dbt to move faster, build trust, and scale with confidence. [Explore dbt](https://www.getdbt.com/product/dbt) *** ## Data teams trust dbt + Snowflake Leading organizations use dbt and Snowflake to reduce the cost of producing insights and improve trust in data. ### Siemens implements a data mesh architecture at scale with dbt Cloud > “Already in our first dbt Cloud project we were amazed by the seamless collaboration dbt Cloud offers, allowing us to effortlessly work together on the same Snowflake project. With built-in tests, simple job scheduling, and easy deployment, dbt Cloud enabled us to immediately focus on the business case rather than spending time on our data architecture setup.” [Read more](https://www.getdbt.com/case-studies/siemens) ### HubSpot empowers analysts to own their tools with dbt > "We think empowering analysts to own their tools is the only way to build a productive analytics team at scale. dbt makes it easier to do data modeling the right way, and harder to do it the wrong way." [Read more](https://www.getdbt.com/case-studies/hubspot) ### Enpal fuels data efficiency with dbt and saves 70% on data costs > “We used to have outages on a regular basis where the organization wouldn’t have updated data for a whole day. This year, we’ve only had three or four minor hiccups that we could fix in a few hours.” [Read more](https://www.getdbt.com/case-studies/enpal) *** *Additional resources* ## Go further with dbt + Snowflake. Learn about how dbt supports AI use-cases from architecture to implementation. ### dbt: The control plane for data collaboration at scale ### dbt Developer Day ### Accelerating dbt with SDF *** ## Learn how to optimize your Snowflake stack with dbt today. Schedule a demo to see how dbt enhances your Snowflake investment, accelerates workflows, and delivers better analytics outcomes. [Book your demo](https://www.getdbt.com/contact) | [Quick start: dbt + Snowflake](https://docs.getdbt.com/guides/snowflake?step=1) --- --- title: "dbt Certification - About" description: "Earn your dbt certification and validate your dbt skills and stand out in the data industry with a recognized certification." url: "https://www.getdbt.com/dbt-certification" --- # Stand apart with a dbt Certification Prove your skills by getting dbt Certified. Analytics Engineers are in high demand, and certifications ensure that your value is recognized. [Register now](https://pages.talview.com/dbtlabs/certifications/) *** ## Choose your certification Select the certification that fits your skills and professional goals. Both exams are available online, require basic SQL proficiency, and are best for those with at least 6 months of dbt experience. Prove your proficiency, and grow your career with dbt and Analytics Engineering certifications. #### dbt Analytics Engineering Certification Exam Demonstrate your ability to build, test, and maintain models to make data accessible to others. #### dbt Architect Certification Exam Showcase your skill to configure, troubleshoot, and optimize projects, as well as manage dbt connections and environments. [Register now](https://pages.talview.com/dbtlabs/certifications/) *** [Watch video](https://getdbt.wistia.com/medias/j0tynfkphm) *** *Watch now* ## Get ready for your exam Prepare with confidence as one of our dbt Certification experts walks you through how to best prepare for your certification exam in this video. [Register now](https://pages.talview.com/dbtlabs/certifications/) *** ## Prove your abilities and accelerate your career Advance your career by getting your skills tested and verified by dbt Lab's team members. If you’ve peeked at our [job board](https://app.slack.com/client/T0VLPD22H/C7A7BARGT) lately, you'll know that demand for experienced analytics engineers is on the rise. With a dbt Certification, you can: - **Stand out to recruiters and hiring managers** with a digital badge that can be shared on your resume and social profiles. - **Validate your skills to current and future employers **who know that dbt is the industry standard for shipping reliable data. - **Distinguish yourself when networking **or collaborating with your peers in the data community. [Register now](https://pages.talview.com/dbtlabs/certifications/) *** ## Frequently asked questions ### How is the exam delivered? Where do I sign up? The exam is delivered online and is proctored. To sign up, [schedule a time](https://pages.talview.com/dbtlabs/certifications/). ### What is the registration fee? The registration fee for the online, proctored exam is $200. ### What are the setup requirements for taking the exam remotely? Remote exam details can be found in the [system requirements and setup instructions](https://www.talview.com/en/test-taker-guide). ### Is the exam available in languages other than English? Yes, in addition to English, the dbt Architect exam and the dbt Analytics Engineering Certification are available in Japanese. The dbt Architect exam is also available in French. ### How is the exam scored? The exam is scored on a point basis, with one point for each correct answer and zero points for incorrect answers. All questions are weighted equally. An undisclosed number of _unscored_ questions will be included on each exam. These are unmarked and indistinguishable from scored questions. Answers to these questions will be used for research purposes only and will not count toward your score. ### Can we access which questions were answered incorrectly? We cannot reveal more than what is included in the score report to avoid compromising the exam’s integrity. ### Is the final score reported as a percentage or a number? Immediately after completing the exam, you will receive your result (pass or fail), and also the percentage of scored questions answered correctly, not a number of questions. ### What is the retake policy? If you do not pass the exam, you may schedule a retake after your last attempt. A $200 registration fee applies for each retake. ### What is the cancellation policy? You can cancel or reschedule an exam at no cost by contacting Tavliew at least 24 hours before your appointment. If you cancel less than 24 hours before your appointment, your payment will be forfeited. ### What kinds of questions can I expect on the exam? Each exam will include a range of question formats, including: - [Multiple-choice](https://support.caveon.com/hc/en-us/articles/6177438689172-Multiple-Choice-Items-in-Scorpion-Explained) - [Fill-in-the-blank](https://support.caveon.com/hc/en-us/articles/7272596297620-Fill-in-the-Blank-Items-in-Scorpion-Explained) - [Matching](https://support.caveon.com/hc/en-us/articles/7110003867284-Matching-Items-in-Scorpion-Explained) - [Hotspot](https://help.blackboard.com/Learn/Instructor/Original/Tests_Pools_Surveys/Question_Types/Hot_Spot_Questions) - [Build list](https://support.caveon.com/hc/en-us/articles/7110892165396-Build-List-Items-in-Scorpion-Explained) - [Discrete Option Multiple Choice](https://domc.caveon.com/about) (DOMC) ### When will I get my results? You will learn whether you’ve passed or failed immediately after completing the exam. ### What will I get with a passing score? Those who pass receive: - A digital badge from [Accredible](https://accredible.com/) which you can add to social profiles, resumes, and personal or professional websites. - A digital certificate for printing and framing. ### Does the certification expire? All dbt Labs certifications are valid for two years from the date awarded. ### Which browsers are supported for online proctoring? Google Chrome, Microsoft Edge, Mozilla Firefox & Apple Safari. [Visit this page for more details.](https://support.caveon.com/hc/en-us/articles/360040429392-Supported-Web-Browsers-for-Caveon-Products) ### Where can I ask questions not covered in this FAQ? Reach out to us at [certification@dbtlabs.com](mailto:certification@dbtlabs.com) to ask your certification questions. ### How can I purchase a bulk of vouchers? Your sales account manager can process a purchase of vouchers, and include any applicable discount. ### Is the exam open-book? The exam is not open book. Test takers are not allowed to bring notes or resources into the exam room. ### Do you support accommodations for test takers with disabilities? For accommodation requests, please contact us via email at [accessibility@dbtlabs.com](mailto:accessibility@dbtlabs.com) *** ## Schedule your exam today Certify your skills by scheduling your exam through our partner Talview. You can test online and get proof your skills immediately after you pass. [Register now](https://pages.talview.com/dbtlabs/certifications/) --- --- title: "Training" description: "Expert-led dbt training by the team that created dbt. On-demand courses, live workshops, & team programs — for all skill levels. Start learning free." url: "https://www.getdbt.com/dbt-learn" --- # Expand your skills. Empower your team. The dbt Labs team offers live and on-demand training to help individuals and teams move faster, build better, and grow their data and AI careers. [Start learning now](https://learn.getdbt.com/catalog) | [Explore on-demand webinars](https://www.getdbt.com/resources/webinars) *** ## Stay ahead of the curve with dbt training. Top data professionals learn to evaluate platform capabilities, gain in-demand skills, and master best practices by training with dbt—accelerating their analytics career and organizational impact. ### Expert-led training Our experts help you evaluate dbt's capabilities, gain practical insight, and get hands-on with key platform features ### Courses for every level From beginner to enterprise leader, dbt courses are tailored to help you master the features that matter most to your needs ### Flexible formats Access live training sessions or learn at your own pace with on-demand resources ### Career advancement Invest in your professional growth by learning dbt sklils—the most sought-after skills in data *** *Courses overview* ## Courses designed for maximum impact. It's easy for everyone to get well-versed in dbt, no matter their learning style. ### Explore on-demand webinars Deepen your skills with our on-demand webinars and stay tuned for our next wave of live workshops. [View on-demand webinars](https://www.getdbt.com/resources/webinars/category/on-demand) ### On-demand Flexible training modules are available at any time—perfect for self-paced learning [Start learning](https://learn.getdbt.com/catalog) ### Enterprise team packages Tailored training solutions designed for larger teams to scale their dbt expertise [Contact sales](https://www.getdbt.com/contact) *** *Explore our courses* ## Level up with expert-built dbt courses. Evaluate dbt's capabilities firsthand by exploring its interface, powerful features, and practical use-cases through courses built and led by dbt experts. *** *Powered by dbt* ## Training is just the beginning. dbt gives you the tools to put what you learn into action—for faster builds, stronger governance, and production-grade workflows across your data stack. ### Explore dbt capabilities From CI/CD to the Semantic Layer, see everything dbt can do for your data team [View platform capabilties](https://www.getdbt.com/product/dbt) ### Integrate with your stack Snowflake, Databricks, Redshift, BigQuery, Microsoft Fabric, Fivetran—dbt works where your data lives [See integrations](https://www.getdbt.com/product/integrations) ### Go from learning to shipping Turn knowledge into results with tested, production-grade pipelines in dbt [Start a free trial](https://www.getdbt.com/signup) *** *Join 100,000+ data professionals* ## Great data work never happens alone. The dbt Community connects you with thousands of data practitioners, leaders, and learners—all solving real problems, sharing best practices, and growing their careers together. - - - [Join the Community](https://www.getdbt.com/community/join-the-community) | [Explore Community resources](https://www.getdbt.com/community) --- --- title: "Legal - The dbt Product Licensing Agreement" url: "https://www.getdbt.com/dbt-product-license-agreement" --- _This license applies to the dbt Product. Source Code for dbt OSS is available at [github.com/dbt-labs/dbt](https://github.com/dbt-labs/dbt) under the [Apache 2.0 license agreement](https://github.com/dbt-labs/dbt/blob/main/LICENSE). Additional license information can be found in our FAQ at https://www.getdbt.com/licenses-faq._ ### The dbt Product Licensing Agreement BY DOWNLOADING AND/OR USING THE PRODUCTS AS DEFINED BELOW, YOU AGREE TO THIS AGREEMENT. This dbt Product Licensing Agreement (“**Agreement**”) is between dbt Labs, LLC (“**Provider**”) and the party (“**User**”) using dbt (“**dbt**”) and the dbt Extension for Visual Studio Code software (“**VS Code Extension**”) (or similar successor products) and its associated Documentation (each, a “**Product**”, and collectively, the “**Products**”). If you are agreeing on behalf of an organization, you represent and warrant that you have the authority to bind that organization, and every reference to “User” hereinafter shall be deemed to refer to such organization. The Effective Date hereof is the date of the first use or download of the Product by User. IF USER DOES NOT ACCEPT THIS AGREEMENT, THEN USER MAY NOT USE THE PRODUCTS. #### 1. Definitions. Capitalized terms shall have the meanings defined herein. “**Documentation**” means the Product documentation made available by Provider on Provider’s website at docs.getdbt.com, as may be updated from time to time. “**End User**” means clients or other third parties authorized by the User who use the Products in connection with User’s products and/or services. **“Platform Feature**” means any dbt Platform feature, including those that utilize or access generative artificial intelligence and/or large language models, that is made available by Provider through the Products when an account is created for a User, as well as any updates thereto. Provider may determine, in its sole discretion, which features are Platform Features. #### 2. Provision of the Product; Ownership. 2.1 _License to Product_. Subject to User’s compliance with the Agreement, Provider grants User a limited, non-exclusive, non-transferable, non-sublicensable license for User to (i) download, install, run, and use the Products; and if applicable, (ii) redistribute the Products to third parties, observing the restrictions in Sections 3 and 4. 2.2 _IP Ownership._ This Agreement does not transfer to User any Provider or third party intellectual property rights. As between Provider and User, Provider owns all right, title, and interest in and to the Products (including any improvements, modifications, and enhancements thereto). All rights not expressly granted by Provider herein are reserved. 2.3 _Data Collection_. The Products may collect and send to Provider information about User and User’s use of the Products. Provider may use this information to enforce this Agreement and to provide, support, and improve the Products and Provider’s products and services. User may opt-out of certain information collection scenarios as described at [https://docs.getdbt.com/docs/local/dbt-networking-requirements](https://www.getdbt.com/). User can learn more about such data practices in Provider’s Privacy Policy at https://www.getdbt.com/cloud/privacy-policy. User’s use of the Products operates as User’s consent to these practices. In the event any User data includes personal data, Provider will process such information in accordance with its Data Processing Agreement available at https://www.getdbt.com/dbt-assets/cloud/dpa. #### 3. User Responsibilities; Restrictions. 3.1 _User Responsibilities_. User is fully responsible for all activity that occurs pursuant to its use of the Products, regardless of whether undertaken by User, its employees, or a third party (including End Users, contractors, or agents). 3.2 _Use Restrictions._ With respect to the use of the Products, User shall not, and shall not permit or encourage any third party to: 1. in whole or in part, reverse-engineer, decompile, disassemble, or attempt to discern or derive the source code; 2. attempt to or interfere with, disable, or circumvent any access control functionalities, (including gating, license or entitlement validation, or User login, or any functionality that causes the Products to interact with the dbt Platform or online services of Provider); 3. remove, alter, or obscure Provider’s proprietary rights notices or restrictive legends (including copyright, patent, and trademark notices and symbols); 4. use the Products in any way that is in breach of applicable laws. Provider may terminate this Agreement if User has materially breached this Agreement and fails to cure such breach within 30 days of receiving written notice thereof, or immediately terminate if such material breach is incapable of cure. Upon termination of this Agreement, all licenses contained in this Agreement will automatically terminate and User shall discontinue all use of the Products (and communicate such termination to End Users, if applicable). 3.3 _Platform Feature Access_. User understands and agrees that User and any End User must create an account with Provider using a verified email address to access and use the Platform Features. Such access and use will be governed by separate terms, and not by this Agreement. #### 4. Redistribution _The following only applies if User makes the Product available to End User(s) (e.g., by embedding the Products into User’s own product, then making available such product to third parties), whether via on-premises download or via online access._ 4.1. User acknowledges that the Products’ access to and interaction with Platform Features is substantial consideration for granting the rights in this Agreement. User must ensure that User’s integration of the Products preserves the End User’s ability to freely access the Provider’s products and services including, but not limited to, the Products, the Platform Features, dbt Platform account creation and End User login, as well as provision of support services by Provider, all in accordance with the Documentation. Upon Provider's request, User must facilitate in good faith Provider's reasonable requests for communication between Provider and End User(s), in such a manner that preserves the End User’s user experience for interacting with the Products. Without limiting the foregoing, User must not obstruct, block or introduce obstacles or delays that have the effect of hampering or interfering with (a) communication between Provider and End User, (b) User’s ability to view, access, or use the Products, the dbt Platform, and/or any Platform Features, or (c) the Products from sending telemetry data to Provider. User may not share, pool, or relay its own login credentials to any End User and is solely responsible for ensuring its redistribution complies with this Agreement and any applicable law. 4.2 _Provider Name_. While this Agreement is in effect, User may make reasonable use of Provider name and logos in connection with permitting access to the Product by End Users to the extent that User complies with Provider's Trademark Policy and Brand Guidelines at these links: [https://www.getdbt.com/dbt-assets/dbt-trademark-guidelines](https://www.getdbt.com/) (Trademark Policy) and [https://www.getdbt.com/brand-guidelines](https://www.getdbt.com/) (Brand Guidelines) (or such successive links as may be provided to User after the Effective Date hereof) and cooperates with any written instructions provided by Provider. #### 5. Feedback. Upon User submitting any suggestions, proposals, ideas, recommendations, or other feedback regarding the Products, User grants to Provider a royalty-free, fully paid, sublicensable, transferable, non-exclusive, irrevocable, perpetual, worldwide right and license to make, use, and otherwise utilize such feedback without attribution, compensation, or restriction. These rights survive this Agreement. #### 6. Disclaimer; Third Party Products. 6.1 _Warranty Disclaimer._ USE OF THE PRODUCTS IS AT USER’S SOLE RISK AND THE PRODUCTS ARE PROVIDED “AS IS” AND “AS AVAILABLE.” TO THE MAXIMUM EXTENT PERMITTED BY APPLICABLE LAW, PROVIDER MAKES NO EXPRESS WARRANTIES AND DISCLAIMS ALL WARRANTIES, REPRESENTATIONS AND CONDITIONS, EXPRESS OR IMPLIED, INCLUDING IMPLIED WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. PROVIDER DOES NOT WARRANT ANY THIRD PARTY COMPONENTS OR PRODUCTS. 6.2 _Third Party Components and Products._ The Products may include third party products or components with separate legal notices or governed by other agreements, as may be described in the ThirdPartyNotices file accompanying the Products. In addition, User’s access and use of any third party product or component in connection with the Products shall be subject solely to the corresponding third party’s license or terms, as applicable. To the extent any such terms for a specific third party component prohibit the limitations in this Agreement, such limitations will not apply to such component. Provider shall have no liability of any kind arising from or related to User’s (including its End Users’) access to, use of, or inability to use any third party product or component. #### 7. Limitation of Liability. TO THE MAXIMUM EXTENT PERMITTED BY APPLICABLE LAW, PROVIDER SHALL NOT BE LIABLE FOR ANY INDIRECT, INCIDENTAL, RELIANCE, SPECIAL, PUNITIVE OR CONSEQUENTIAL DAMAGES, INCLUDING PROCUREMENT OF SUBSTITUTE PRODUCTS OR SERVICES OR LOSS OF PROFITS, BUSINESS OPPORTUNITY, ANTICIPATED GOODWILL, REVENUE, DATA OR DATA USE, WHETHER FORESEEABLE OR NOT AND EVEN IF PROVIDER HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGES. THE TOTAL LIABILITY OF PROVIDER ARISING OUT OF OR RELATED TO THIS AGREEMENT WILL NOT EXCEED $10.00. #### 8. Miscellaneous. 8.1 _Trade Laws_. User agrees to comply with, and, if applicable, shall not permit End Users to access or use the Products in violation of international export controls and economic and trade sanctions laws and regulations (collectively, “**Trade Laws**”). Without limiting the foregoing, User represents that it and its End Users (a) will not access the Products from a country or territory that is itself the subject or target of trade or economic sanctions (a “**Sanctioned Country**”). 8.2. _Governing Law and Jurisdiction_. This Agreement shall be governed by the laws of the State of California, without regard to its conflict of laws provisions. This Agreement shall not be governed by the United Nations Convention on Contracts for the International Sale of Goods or the Uniform Computer Information Transactions Act. Any legal action relating to this Agreement must be brought in the courts in San Francisco, California. The parties hereby accept generally and unconditionally the jurisdiction, resolution method, and venue noted above. The prevailing party is entitled to recover all reasonable fees, costs and expenses of enforcing its rights, including reasonable attorneys’ fees. 8.3 _Entire Agreement_; _No Waiver; Severability_. This Agreement constitutes the entire agreement between User and Provider concerning the Product. No waiver will be implied from conduct or failure to enforce or exercise rights under this Agreement. If any provision of this Agreement is held invalid or unenforceable, the remainder of this Agreement will continue in full force and effect. 8.4 _No Third Party Beneficiaries or Joint Relationship_. Nothing in this Agreement shall confer, or is intended to confer, on any third party any benefit or the right to enforce any term of this Agreement, and this Agreement shall not establish any relationship of partnership, joint venture, employment, franchise, or agency between the parties. --- --- title: "dbt Summit 2026 waitlist" url: "https://www.getdbt.com/dbt-summit-2026-waitlist" --- *Early access starts here* ## Enter your details and join the waitlist for 2026 2026 is shaping up to be a big year in data, and you don't want to be late to the party. We're back in Las Vegas with the largest gathering of the dbt community, and it's already shaping up to be bigger than ever. Join the waitlist and be one of the first to know what's coming in 2026. Here's a look at the details for next year's event: - What - Where - When *** ## Take your community connections live dbt Summit is where the dbt Community meets IRL and online—4 days of sessions, keynotes, and conversations you won’t find anywhere else. [Join us at dbt Summit](https://www.getdbt.com/dbt-summit) | [Join the community](https://www.getdbt.com/community) --- --- title: "dbt Charts" description: "Build auditable dashboards with dbt Charts: an open-source YAML language and collaborative BI platform." url: "https://www.getdbt.com/dbtcharts" --- # Charts built for Chat AI agents make an unauditable mess of dashboards. Give them dbt Charts, a simple declarative YAML language, and they build better dashboards you can govern, using fewer tokens. [Try the platform](https://dbtcharts.com/accounts/signup/) | [Explore the OSS language](https://dbtcharts.com/language/) *** *The open-source language* ## Every dashboard should show its work. Queries, charts, layout, and the explanation live in one text file. SQL defines the data, a few declarations describe how to show it, and people and agents read, edit, and review the same file. [How the language works](https://dbtcharts.com/language/) *** ## Declarative design. Interactive charts. ### Confidence should ship with every change. Validate board structure in CI, then check queries against your dbt models or the warehouse. A missing column fails on the branch, not in front of your readers. [Try the platform](https://dbtcharts.com/accounts/signup/) ### Good design should be the default. A good chart makes a comparison easy; a good report says what it means. That craft is built into the defaults, and the renderer flags problems like crowded labels. [Explore charts and themes](https://dbtcharts.com/language/) ### One workflow for models and charts. Boards live beside your dbt models, on the same branch, in the same pull request. Run the same board on your laptop, in CI, and on the platform. Apache 2.0. [Explore the open-source project](https://github.com/dbt-labs/dbt-charts) *** ## Language first BI An open language for the charts. A platform for collaboration, with agents and with each other. ### The language Create boards as YAML that live next to your dbt models and render them on your laptop. [How the language works](https://dbtcharts.com/language/) ### The platform Build conversational analytics on your warehouse using the visual editor and share with permissions. [Explore the platform](https://dbtcharts.com/product/platform/) *** ## Point it at your warehouse. Ask anything. Start with the free workspace. Connect your warehouse and your dbt repo, then ask your first question. [Get started](https://dbtcharts.com/accounts/signup/) | [View Quickstart Guide](https://docs.getdbt.com/guides/dbt-charts?step=1&version=2) --- --- title: "Home" description: "dbt Labs empowers data teams to build reliable, governed data pipelines—accelerating analytics and AI initiatives with speed and confidence." url: "https://www.getdbt.com" --- # Community Keynote Celebrate the dbt community and look ahead as dbt Core and Fusion unite under one framework — dbt — and we continue building in the open. [Register now](https://www.getdbt.com/dbt-summit/registration/online) *** - phData - Nasdaq - Affirm - Toyota - Omni - CHG Healthcare - Siemens - Infinite Lambda *** Fivetran and dbt are one company. Here's what that means. *** ### Powered by the brand new Fusion engine, dbt makes data teams extraordinarily productive as they build data models—whether locally or in the cloud. *** ## Interoperable by design dbt never stores your data. Lean on our deep ecosystem integrations and commitment to open standards to securely, scalably, and flexibily get your data from where it lives to where it needs to go. - Tableau - Fivetran - OpenAI - Snowflake - Azure AI - Databricks *** *Transform your outcome* ## Choose dbt for speed, trust, and delivering real results. Standardize on dbt to boost data quality, strengthen governance, and encourage collaboration so your teams can deliver trusted analytics and AI products faster than ever. ### Improve data quality and trust Rich metadata powers dbt Catalog and lineage, improving governance and trusted data for analytics and AI development. [Build trust in data](https://www.getdbt.com/product/dbt-catalog) ### Drive efficiency & reduce cost dbt helps teams spot inefficiencies, automate routine work, and use compute smarter—cutting costs and speeding delivery. [See how dbt streamlines work](https://www.getdbt.com/product/cost-optimization) ### Build better AI with higher-quality data dbt ensures your data is trusted, governed, and properly documented — so AI gets built on the best possible inputs [dbt for powerful AI](https://www.getdbt.com/product/ai) *** *Optimize costs* ## Smarter orchestration saves 30%+ on warehouse spend Fusion brings stateful intelligence to your production pipelines. Automatically build only the models that need to be updated—no rewrites or complex setup required. Save on unnecessary compute, maintain your SLAs, and keep your projects running fast. [Schedule a cost-saving consult](https://www.getdbt.com/contact) *** ## Works with your IDEs Get a native, local development experience in your favorite IDE. 
Use the IDE extension with Cursor, Claude Code, Windsurf or VS Code. [Get started with dbt](#) | [this is button](#) *** *dbt in the field* ## Find dbt everywhere We'll be at Snowflake Summit and Databricks Data+AI Summit in June, then hosting our own dbt Summit in September at The Cosmopolitan in Las Vegas. ### Visit us at Databricks Data+AI Summit Your AI needs what your data already knows. Stop by booth #430 for live demos, product features, and guest speakers. ### Biggest dbt event of the year Join the world’s largest gathering of dbt users, where data leaders and practitioners come together to shape the future of data analytics and AI. [Find out more](https://www.getdbt.com/dbt-summit) *** *The dbt Community* ## Join the largest community shaping the future of data & AI The dbt Community is your gateway to best practices, innovation, and direct collaboration with thousands of data leaders and AI practitioners worldwide. Ask questions, share insights, and grow alongside a welcoming network of builders. [Join the Community](https://www.getdbt.com/community/join-the-community) | [Explore the Community](https://www.getdbt.com/community) --- --- title: "Energy & Utilities" url: "https://www.getdbt.com/industry/energy-utilities" --- # Transform complexity into clarity for energy & utilities. With dbt, energy and utility companies can modernize legacy systems, standardize reporting, and gain the transparency needed to meet regulatory requirements and sustainability goals. [Talk to an energy data expert today](https://www.getdbt.com/contact) *** ## Common use cases in Energy & Utilities Energy and utilities companies must manage massive amounts of operational data while meeting strict compliance requirements and advancing sustainability goals. These are the high-impact ways dbt helps providers, distributors, and regulators stay compliant, resilient, and future-ready. ### Regulatory compliance & auditability Ensure energy production and usage data meets standards like FERC, NERC, and ESG reporting frameworks. With built-in version control, audit logging, and lineage, dbt makes it easy to prove compliance, reduce reporting risk, and maintain trust with regulators and stakeholders. ### Reliable emissions & grid reporting Establish a single, trusted source of truth across generation, distribution, and consumption data. dbt enforces consistency and transparency, reducing errors and enabling more reliable reporting for compliance filings, emissions tracking, and investor disclosures. ### Protect critical infrastructure data Protect sensitive operational data with role-based access controls, encryption, and secure architecture. dbt helps energy and utilities organizations safeguard critical infrastructure data while aligning with global compliance and cybersecurity standards. ### Scale energy & customer workloads Handle complex, large-scale energy and grid data workloads without sacrificing speed or stability. dbt’s cloud-native architecture supports smart grid analytics, renewable integration, and enterprise growth, even as data volumes and regulatory demands increase. *** > > > — Jared Stout *** ## Unlocking new data use cases dbt helps utilities, clean-energy, and energy producers turn meter, asset, production, and customer data into resilient products that drive reliability, efficiency, and growth. ### Accelerating modernization Standardize transformations across AMI, SCADA, IoT, and production systems to move from brittle reporting to a cloud-ready, analytics-first foundation, opening doors to use cases like predictive maintenance. ### Customer, grid & protection 360 Combine meter, billing, service, network, and production data to optimize programs (demand response, EV, DER, exploration), reduce churn, and improve reliability. ### Data products & self-service at scale Package curated models for field ops, grid planning, production optimization, and customer teams—enabling rapid experimentation and faster rollout of rates, programs, and projects. *** ## Drive sustainability and resilience with compliant, trusted data dbt brings transparency and agility to energy and utilities data — supporting regulatory reporting, ESG goals, and reliable operations at scale. ### Standardized data transformation with built-in governance SQL-based transformations deliver traceability, version control, and reproducibility, ensuring compliance with FERC, NERC, and ESG standards. Automated documentation and CI/CD processes help teams meet audit requirements without slowing operations. ![Image](https://cdn.sanity.io/images/wl0ndo6t/main/c41f92b34c111a4325b1e0a0e1aa831f53cbd610-1224x1224.png) ### Data lineage & auditing for compliance Gain end-to-end visibility across energy production, consumption, and emissions data. With lineage and detailed audit trails, dbt simplifies regulatory reporting and ESG disclosures while reducing the risk of costly compliance errors. ![Image](https://cdn.sanity.io/images/wl0ndo6t/main/1a8f2e3ded71f528a499b38aadfc927decc1435d-1224x1224.png) ### Security & compliance-ready architecture Safeguard sensitive grid, utility, and infrastructure data with granular access controls, IAM integration, and encryption. dbt’s architecture aligns with cybersecurity standards for critical infrastructure, reducing risk across the enterprise. ![Image](https://cdn.sanity.io/images/wl0ndo6t/main/70a4ee9323e22a37db20b314693d121e4a52968f-1232x1072.png) ### Collaboration between data, compliance, and business teams Bring engineers, compliance officers, and operations teams together on a single source of truth. Centralized governance ensures consistency while enabling cross-team collaboration on sustainability, reporting, and operational initiatives. ![Image](https://cdn.sanity.io/images/wl0ndo6t/main/5e6ccb3846e07382de34777c4b1781356cbebf5b-1039x897.png) ### Scalability without losing control Energy and utilities face rapidly growing data volumes from smart meters, renewable sources, and IoT devices. dbt’s cloud-native platform scales seamlessly while maintaining centralized governance and data security. ![Image](https://cdn.sanity.io/images/wl0ndo6t/main/c2158e82ae9ec7037c359f207849f4ae7da7a631-1224x1224.png) *** ## Leading energy and utility providers choose dbt for trusted data From renewable pioneers to critical water services, organizations like Enpal, Sunrun, and Watercare rely on dbt to modernize infrastructure, meet compliance standards, and accelerate the transition to sustainable energy. ### Enpal delivers solar data pipelines with dbt to ensure compliance and accelerate renewable growth ### Sunrun unifies solar energy data with dbt for transparency, scalability, and efficient operations ### Watercare modernizes data workflows with dbt to improve reporting accuracy and meet compliance needs *** ## Trusted globally. Proven at scale. ### 97% customer satisfaction Rated 4.8/5 on G2 by thousands of data leaders who trust dbt Cloud for critical analytics and AI initiatives ### Enterprise-grade compliance ### 80,000+ teams Over 80,000 teams worldwide rely on dbt, processing billions of data transformations with confidence ### Named a Leader
by Snowflake and Databricks Recognized as Snowflake Data Cloud Partner of the Year and Databricks Customer Impact Partner of the Year *** *The dbt Community* ## Join the largest community shaping data The dbt Community is your gateway to best practices, innovation, and direct collaboration with thousands of data leaders and AI practitioners worldwide. Ask questions, share insights, and build better with the experts. [Join the Community](https://www.getdbt.com/community/join-the-community) | [Explore the Community](https://www.getdbt.com/community) --- --- title: "Financial Services" url: "https://www.getdbt.com/industry/financial-services" --- # Modernize your data. Minimize your risk. Financial data moves fast — and regulations move faster. With dbt, you can transform, govern, and audit data with confidence. [Talk to a financial data expert today](https://www.getdbt.com/contact) *** *dbt for Financial Services* ## Common use cases in Financial Services Financial institutions face the dual challenge of driving innovation while meeting strict compliance requirements. These are the high-impact ways dbt helps leading banks, insurers, and fintechs stay agile, compliant, and competitive. ### Regulatory compliance & auditability Ensure data transformations, definitions, and usage meet stringent standards like SOX, PCI DSS, EU DORA and GDPR. With built-in version control, audit logging, and lineage, dbt makes it easy to prove compliance at every step. ### Trusted financial reporting Establish a single, trusted source of truth with standardized definitions and metrics. dbt enforces consistency, quality, and transparency across teams, reducing errors and enabling faster, more reliable reporting. ### Protect customer & transaction data Protect sensitive financial data with role-based access controls, encryption, and secure architecture. dbt aligns with industry regulations to safeguard customer trust and minimize operational risk. ### Scale high-volume financial data Handle complex, large-scale financial data workloads without sacrificing speed or stability. dbt’s cloud-native architecture and project management features enable growth and agility, even as regulatory demands increase. *** > > > — Amber Oar *** ## Unlocking new data use cases Beyond compliance, dbt empowers financial institutions to accelerate transformation and unlock new business value. ### Accelerating modernization Speed up digital transformation by reducing time-to-insight and enabling faster adoption of analytics and AI initiatives. ### Customer 360 & breaking down silos Unify customer data across products and channels to support personalized experiences, better pricing, loan decisions, and improved retention, while enabling quicker, data-driven responses to shifting market conditions. ### Data governance for AI readiness Build a governed, high-quality data foundation that ensures AI and machine learning models are trusted, compliant, and enterprise-ready. *** ## Accelerate innovation while maintaining compliance and resiliency dbt brings trust, compliance, and agility to financial data. Unlike competitors, the dbt platform improves compliance posture, ensures governance at scale, and increases adoption across teams. ### Standardized data transformation with built-in governance SQL-based transformations deliver traceability, strict CI process, version control, and reproducibility. Automated documentation and fast dev cycles help teams meet compliance without slowing down. ![Image](https://cdn.sanity.io/images/wl0ndo6t/main/c41f92b34c111a4325b1e0a0e1aa831f53cbd610-1224x1224.png) ### Data lineage & auditing for compliance SQL-based transformations deliver traceability, strict CI process, version control, and reproducibility. Automated documentation and fast dev cycles help teams meet compliance without slowing down. ![Image](https://cdn.sanity.io/images/wl0ndo6t/main/1a8f2e3ded71f528a499b38aadfc927decc1435d-1224x1224.png) ### Security & compliance-ready architecture Granular access controls, enterprise IAM integration, encryption, SOC 2 certification, and adherence to global data retention laws help reduce risk and tool sprawl. ![Image](https://cdn.sanity.io/images/wl0ndo6t/main/70a4ee9323e22a37db20b314693d121e4a52968f-1232x1072.png) ### Collaboration between data, compliance, and business teams Self-serve analytics with controlled governance unite compliance teams and data engineers. Centralized metadata reduces the risk of errors and enables faster cross-team alignment. ![Image](https://cdn.sanity.io/images/wl0ndo6t/main/5e6ccb3846e07382de34777c4b1781356cbebf5b-1039x897.png) ### Scalability without losing control Seamlessly works with Snowflake, Databricks, BigQuery, and Redshift for large-scale, real-time transformations. Centralized governance keeps data secure while enabling agility for business users. ![Image](https://cdn.sanity.io/images/wl0ndo6t/main/c2158e82ae9ec7037c359f207849f4ae7da7a631-1224x1224.png) *** ## See how leading financial brands use dbt Explore how Bilt Rewards, USAA, and LendInvest use dbt to modernize infrastructure, improve compliance, and deliver better customer experiences. ### USAA proves transformation at scale doesn’t have to break the bank—or the rules ### Bilt Rewards leveraged dbt for audit-ready analytics that cost 80% less and scale on autopilot ### Learn how LendInvest avoids FCA penalties with proactive, error‑catching pipelines *** ## Trusted globally. Proven at scale. ### 97% customer satisfaction Rated 4.8/5 on G2 by thousands of data leaders who trust dbt Cloud for critical analytics and AI initiatives ### Enterprise-grade compliance ### 80,000+ teams Over 80,000 teams worldwide rely on dbt, processing billions of data transformations with confidence ### Named a Leader
by Snowflake and Databricks Recognized as Snowflake Data Cloud Partner of the Year and Databricks Customer Impact Partner of the Year *** *The dbt Community* ## Join the largest community shaping data The dbt Community is your gateway to best practices, innovation, and direct collaboration with thousands of data leaders and AI practitioners worldwide. Ask questions, share insights, and build better with the experts. [Join the Community](https://www.getdbt.com/community/join-the-community) | [Explore the Community](https://www.getdbt.com/community) --- --- title: "Healthcare & Life Sciences" url: "https://www.getdbt.com/industry/healthcare" --- # Modernize your data. Protect patient trust. Healthcare data is complex. Regulations are strict. With dbt, you can transform, govern, and audit data with confidence, ensuring HIPAA-compliant, high-quality insights across the system. [Talk to a healthcare data expert today](https://www.getdbt.com/contact) *** ## Common use cases in Healthcare & Life Sciences Healthcare organizations face the challenge of unlocking insights from complex, sensitive data while meeting strict privacy and regulatory requirements. These are the high-impact ways dbt helps providers, payers, and life sciences organizations stay compliant, secure, and innovative. ### Regulatory compliance & auditability Ensure patient data transformations, definitions, and usage comply with standards like HIPAA, GDPR, and FDA 21 CFR Part 11. With built-in version control, audit logging, and lineage, dbt makes it easy to prove compliance and maintain trust. ### More reliable reporting for patient outcomes Establish a single, trusted source of truth with standardized definitions across clinical, research, and operational data. dbt enforces consistency and transparency, reducing errors and enabling more reliable reporting for patient outcomes and research trials. ### Protect sensitive patient and research data Protect sensitive patient and research data with role-based access controls, encryption, and secure architecture. dbt helps healthcare and life sciences organizations safeguard protected health information (PHI) while aligning with regulatory standards. ### Handle large scale healthcare data workloads Handle complex, large-scale healthcare and genomic data workloads without sacrificing speed or stability. dbt’s cloud-native architecture supports interoperability, clinical research pipelines, and enterprise growth, even as data volumes and regulatory demands increase. *** > > > — William Møller *** ## Unlocking new data use cases dbt helps providers, payers, and health‑tech firms accelerate transformation and unlock new clinical and operational value. ### Accelerating modernization Reduce time‑to‑insight with a scalable transformation layer that speeds delivery of trusted clinical, payer, and operational analytics. ### Patient & member 360 Unite EHR, claims, device, and engagement data to power coordinated care, risk stratification, and personalized experiences. ### Data products & self-service at scale Turn best‑practice models into reusable data products with rich docs and tests, so clinical ops, population health, and finance teams can self‑serve and iterate faster. *** ## Advance healthcare innovation while protecting trust dbt enables secure, compliant, and auditable data pipelines so healthcare and life sciences teams can accelerate research, improve care, and maintain HIPAA/FDA compliance. ### Standardized data transformation with built-in governance SQL-based transformations deliver traceability, version control, and reproducibility, ensuring data pipelines can be trusted for clinical, research, and operational use. Automated documentation supports HIPAA and FDA audit requirements without slowing teams down. ![Image](https://cdn.sanity.io/images/wl0ndo6t/main/c41f92b34c111a4325b1e0a0e1aa831f53cbd610-1224x1224.png) ### Data lineage & auditing for compliance Track every transformation and dependency with column-level lineage and detailed audit trails. dbt makes it easy to demonstrate compliance with HIPAA, GDPR, and FDA 21 CFR Part 11, reducing the risk of reporting errors or gaps in patient data workflows. ![Image](https://cdn.sanity.io/images/wl0ndo6t/main/1a8f2e3ded71f528a499b38aadfc927decc1435d-1224x1224.png) ### Security & compliance-ready architecture Protect sensitive health data with granular access controls, IAM integration, and encryption. dbt’s secure architecture aligns with healthcare compliance frameworks and safeguards protected health information (PHI) across cloud environments. ![Image](https://cdn.sanity.io/images/wl0ndo6t/main/70a4ee9323e22a37db20b314693d121e4a52968f-1232x1072.png) ### Collaboration between data, compliance, and business teams Enable cross-team collaboration by uniting compliance officers, data engineers, and clinical researchers around a single source of truth. Centralized governance ensures consistency while supporting self-service analytics for faster, safer decision-making. ![Image](https://cdn.sanity.io/images/wl0ndo6t/main/5e6ccb3846e07382de34777c4b1781356cbebf5b-1039x897.png) ### Scalability without losing control Healthcare and life sciences data grows rapidly — from patient records to genomic research. dbt’s cloud-native architecture scales with your needs, while centralized governance keeps sensitive data secure and compliant at every stage. ![Image](https://cdn.sanity.io/images/wl0ndo6t/main/c2158e82ae9ec7037c359f207849f4ae7da7a631-1224x1224.png) *** ## Trusted by healthcare and life sciences leaders worldwide Explore how organizations like Firefly Health, Moderna, and Roche use dbt to modernize infrastructure, ensure compliance, and accelerate innovation in healthcare and life sciences. ### Firefly Health uses dbt to strengthen testing, ensure compliance, and drive innovation in digital healthcare ### Moderna uses dbt Mesh to scale research data, fueling AI innovation and faster scientific breakthroughs ### Roche unifies data across teams with dbt, enabling AI adoption and consistent, trusted healthcare insights *** ## Trusted globally. Proven at scale. ### 97% customer satisfaction Rated 4.8/5 on G2 by thousands of data leaders who trust dbt Cloud for critical analytics and AI initiatives ### Enterprise-grade compliance ### 80,000+ teams Over 80,000 teams worldwide rely on dbt, processing billions of data transformations with confidence ### Named a Leader
by Snowflake and Databricks Recognized as Snowflake Data Cloud Partner of the Year and Databricks Customer Impact Partner of the Year *** *The dbt Community* ## Join the largest community shaping data The dbt Community is your gateway to best practices, innovation, and direct collaboration with thousands of data leaders and AI practitioners worldwide. Ask questions, share insights, and build better with the experts. [Join the Community](https://www.getdbt.com/community/join-the-community) | [Explore the Community](https://www.getdbt.com/community) --- --- title: "Manufacturing" url: "https://www.getdbt.com/industry/manufacturing" --- # Power production with reliable, transparent insights. With dbt, manufacturers gain a single source of truth for data, enabling operational efficiency, compliance, and faster decision-making across teams. [Talk to a manufacturing data expert](https://www.getdbt.com/contact) *** ## Common use cases in Manufacturing Manufacturers face growing pressure to modernize operations, improve quality, and keep supply chains running smoothly while meeting strict compliance and sustainability goals. These are the high-impact ways dbt helps manufacturers drive efficiency, reliability, and innovation. ### Regulatory compliance & auditability Ensure production and supply chain data meets standards like ISO, GMP, and ESG reporting frameworks. With built-in version control, audit logging, and lineage, dbt makes it easy to prove compliance, reduce reporting risk, and maintain trust with regulators and partners. ### Reliable supply chain reporting Establish a single, trusted source of truth across plants, systems, and suppliers. dbt enforces consistency and transparency, reducing errors and enabling more reliable reporting for compliance filings, sustainability tracking, and investor disclosures. ### Protect production & partner data Gain visibility into production lines, resource utilization, and supplier performance. dbt helps manufacturers optimize throughput, minimize downtime, and respond quickly to disruptions with accurate, real-time data. ### Scale complex manufacturing data Handle complex, large-scale manufacturing and logistics data without sacrificing speed or accuracy. dbt’s cloud-native architecture supports smart factory analytics, IoT integration, and enterprise growth—even as global supply chains and regulatory demands intensify. *** > > > — Tobi Humpert *** ## Unlocking new data use cases ### Digital thread & product lifecycle 360 Unify PLM, CAD/BOM, MES, ERP, and QMS to connect design → production → field performance, accelerating innovation and reducing time-to-market. ### Predictive quality & yield optimization Blend sensor, SCADA, and test data to detect process drift early, improve first-pass yield, and reduce scrap and rework. ### Resilient, demand-driven supply chains Integrate supplier, inventory, and logistics data with production signals to improve planning accuracy, reduce downtime, and cut costs. *** ## Unlock smarter, more resilient manufacturing with dbt Manufacturers face pressure to modernize operations, meet global compliance standards, and streamline increasingly complex supply chains. dbt provides a governed, scalable data foundation that reduces risk, increases efficiency, and keeps production lines—and businesses—running smoothly. ### Standardized data transformation with built-in governance Gain traceability and control across supply chain, production, and quality datasets. dbt’s version control, testing, and documentation ensure teams deliver reliable insights that meet ISO and industry-specific compliance standards—without slowing down operations. ![Image](https://cdn.sanity.io/images/wl0ndo6t/main/c41f92b34c111a4325b1e0a0e1aa831f53cbd610-1224x1224.png) ### Data lineage & auditing for compliance Visualize and track how data flows from sourcing and logistics through production and distribution. dbt lineage makes audits faster and more accurate, helping teams prove compliance with trade, safety, and regulatory requirements. ![Image](https://cdn.sanity.io/images/wl0ndo6t/main/1a8f2e3ded71f528a499b38aadfc927decc1435d-1224x1224.png) ### Security & compliance-ready architecture Protect sensitive manufacturing data—from supplier contracts to IoT sensor streams—using dbt’s secure, cloud-native architecture. Role-based access controls and audit trails safeguard intellectual property while aligning with global standards. ![Image](https://cdn.sanity.io/images/wl0ndo6t/main/70a4ee9323e22a37db20b314693d121e4a52968f-1232x1072.png) ### Collaboration between data, compliance, and business teams Break down silos across engineering, operations, and compliance. dbt provides a shared framework where business, technical, and quality assurance teams can build, test, and trust data together—speeding up decision-making without sacrificing rigor. ![Image](https://cdn.sanity.io/images/wl0ndo6t/main/5e6ccb3846e07382de34777c4b1781356cbebf5b-1039x897.png) ### Scalability without losing control Easily scale analytics to handle growing volumes of production and supply chain data. dbt’s modular approach ensures flexibility for innovation while maintaining oversight, so manufacturers can expand capacity without introducing risk. ![Image](https://cdn.sanity.io/images/wl0ndo6t/main/c2158e82ae9ec7037c359f207849f4ae7da7a631-1224x1224.png) *** ## Manufacturers building smarter, faster, and more resilient operations with dbt From global leaders like Siemens to innovators like Inventa and Rivian, manufacturers rely on dbt to streamline production data, improve quality, and scale innovation across complex supply chains. ### Rivian powers a data mesh with dbt to scale EV production and accelerate manufacturing ### Siemens standardizes pipelines with dbt for consistent global operations and faster insights ### Inventa unifies production data with dbt to improve visibility, cut errors, and optimize decisions *** ## Trusted globally. Proven at scale. ### 97% customer satisfaction Rated 4.8/5 on G2 by thousands of data leaders who trust dbt Cloud for critical analytics and AI initiatives ### Enterprise-grade compliance ### 80,000+ teams Over 80,000 teams worldwide rely on dbt, processing billions of data transformations with confidence ### Named a Leader
by Snowflake and Databricks Recognized as Snowflake Data Cloud Partner of the Year and Databricks Customer Impact Partner of the Year *** *The dbt Community* ## Join the largest community shaping data The dbt Community is your gateway to best practices, innovation, and direct collaboration with thousands of data leaders and AI practitioners worldwide. Ask questions, share insights, and build better with the experts. [Join the Community](https://www.getdbt.com/community/join-the-community) | [Explore the Community](https://www.getdbt.com/community) --- --- title: "Telecommunications" url: "https://www.getdbt.com/industry/telecommunications" --- # Modernize your network with reliable data. dbt makes it easier for telecoms to transform, govern, and audit their data, ensuring consistency across global operations. [Talk to a telecom data expert](https://www.getdbt.com/contact) *** ## Common use cases in Telecommunications Telecom providers face constant pressure to modernize networks, improve customer experiences, and comply with strict regulatory standards while managing massive volumes of data. These are the high-impact ways dbt helps telecoms drive agility, reliability, and security. ### Regulatory compliance & auditability Ensure network, customer, and billing data meet telecom regulations like FCC, GDPR, CCPA, and DORA. With built-in version control, audit logging, and lineage, dbt makes it easy to prove compliance, reduce reporting risk, and maintain trust with regulators and enterprise partners. ### Reliable network & customer reporting Establish a single, trusted source of truth across subscriber systems, network operations, and service platforms. dbt enforces consistency and transparency, reducing errors and enabling reliable reporting for regulatory filings, network performance tracking, and customer billing accuracy. ### Protect subscriber & usage data dbt helps telecoms strengthen security, prevent breaches, and minimize risk with accurate, real-time data lineage—supporting strict data residency requirements and customer privacy expectations. ### Scale massive network traffic Handle massive call detail records, real-time streaming data, and growing customer bases without sacrificing speed or accuracy. dbt’s cloud-native architecture supports high-volume analytics, 5G network optimization, and enterprise growth—even as regulatory and infrastructure demands intensify. *** > > > — Quentin Coviaux *** ## Unlocking new data use cases ### Customer & network 360 Unify subscriber, usage, and network performance data to improve churn prediction, optimize pricing, and enhance quality of service. ### Data products & self-service at scale Package curated models for marketing, customer care, and network ops teams, enabling faster rollouts of new services, targeted offers, and network optimizations. ### AI/ML readiness for telco innovation Provide a governed data layer to power AI-driven use cases like predictive maintenance, fraud detection, and personalized recommendations. *** ## Modernize telecom data while meeting compliance and scale demands dbt helps telecom providers unify complex network, customer, and regulatory data. With built-in governance, dbt enables accurate reporting, real-time insights, and scalable architectures to power next-gen connectivity, reduce risk, and accelerate innovation. ### Standardized data transformation with built-in governance Telecom networks generate massive volumes of operational and customer data. dbt enforces version control, traceability, and standardized transformations, ensuring telecom data pipelines meet regulatory standards like CPNI and GDPR. Automated documentation and governance reduce audit overhead while keeping engineering teams focused on innovation. ![Image](https://cdn.sanity.io/images/wl0ndo6t/main/c41f92b34c111a4325b1e0a0e1aa831f53cbd610-1224x1224.png) ### Data lineage & auditing for compliance Track how subscriber, billing, and network data flows across complex systems with full lineage visibility. dbt’s audit logs and lineage features make it easier to demonstrate compliance with telecom regulations, reduce risk of fines, and maintain transparency with regulators and partners. ![Image](https://cdn.sanity.io/images/wl0ndo6t/main/1a8f2e3ded71f528a499b38aadfc927decc1435d-1224x1224.png) ### Security & compliance-ready architecture dbt’s architecture supports secure, compliant data transformations at scale, ensuring encryption, access controls, and compliance reporting requirements are met without slowing performance. ![Image](https://cdn.sanity.io/images/wl0ndo6t/main/70a4ee9323e22a37db20b314693d121e4a52968f-1232x1072.png) ### Collaboration between data, compliance, and business teams Bridge silos between engineering, regulatory, and business operations. dbt’s collaborative workflows make it easier for data teams, compliance officers, and executives to work from the same source of truth, improving decision-making around network reliability, customer experience, and revenue growth. ![Image](https://cdn.sanity.io/images/wl0ndo6t/main/5e6ccb3846e07382de34777c4b1781356cbebf5b-1039x897.png) ### Scalability without losing control Telecom data volumes scale rapidly with 5G adoption and IoT expansion. dbt’s cloud-native foundation ensures you can handle billions of data points across network and customer systems without sacrificing governance or performance. Scale confidently while keeping compliance and reliability intact. ![Image](https://cdn.sanity.io/images/wl0ndo6t/main/c2158e82ae9ec7037c359f207849f4ae7da7a631-1224x1224.png) *** ## Telecom leaders driving reliable, scalable networks with dbt From disruptors like Rebtel to global carriers like Virgin Media O2 and One NZ, telecom providers use dbt to unify network data, accelerate innovation, and deliver better customer experiences at scale. ### Rebtel builds data pipelines with dbt to scale global telecom services ### Virgin Media O2 uses dbt to unify network data and improve customer insights ### One NZ standardizes data with dbt to reduce complexity and speed up decisions *** ## Trusted globally. Proven at scale. ### 97% customer satisfaction Rated 4.8/5 on G2 by thousands of data leaders who trust dbt Cloud for critical analytics and AI initiatives ### Enterprise-grade compliance ### 80,000+ teams Over 80,000 teams worldwide rely on dbt, processing billions of data transformations with confidence ### Named a Leader
by Snowflake and Databricks Recognized as Snowflake Data Cloud Partner of the Year and Databricks Customer Impact Partner of the Year *** *The dbt Community* ## Join the largest community shaping data The dbt Community is your gateway to best practices, innovation, and direct collaboration with thousands of data leaders and AI practitioners worldwide. Ask questions, share insights, and build better with the experts. [Join the Community](https://www.getdbt.com/community/join-the-community) | [Explore the Community](https://www.getdbt.com/community) --- --- title: "dbt Labs 日本" description: "dbt Labs は、ガバナンスの行き届いたデータパイプラインでデータ品質を向上。分析と AI 活用を加速し、運用の効率化とクラウドコストの最適化を同時に実現します。" url: "https://www.getdbt.com/jp" --- # 信頼できるAIエージェントは、データ基盤で決まる dbt は、生データを整理・検証し、アナリティクス・ダッシュボード・AIが使える信頼できるデータに変換するプラットフォームです。 [dbtのアカウントを作成する](https://www.getdbt.com/jp/signup) | [デモを予約する](https://www.getdbt.com/jp/contact) *** - phData - Nasdaq - Affirm - Omni - CHG Healthcare - Siemens - Infinite Lambda *** ### 新搭載の Fusion エンジンにより、dbt はデータチームのモデル構築を劇的に加速します。 ### ローカルでもクラウドでも。 *** *ビジネスに、真の変革を* ## スピード・信頼性・確かな結果、それが dbt が選ばれる理由です dbt を活用することで、無駄を省き、定型作業を自動化し、コストを削減しながらデータ提供のスピードを加速します ### データ品質と信頼性を強化 豊富なメタデータが dbt Catalog とリネージを強化し、アナリティクスおよびAI開発のためのガバナンスと信頼できるデータを改善します。 ### 効率化とコスト削減 dbt を活用することで、無駄を省き、定型作業を自動化し、コストを削減しながらデータ提供のスピードを加速します。 ### 高品質なデータで、AIの精度を高める dbt はデータの信頼性・管理・ドキュメント化を徹底することで、AIが最高の品質のデータをもとに構築される環境を整えます。 ### 既存の業務を止めずに、データ基盤を最新化 dbt でパイプラインの構築・管理を標準化することで、普段の業務やデータに影響を与えることなく、レガシーツールから移行できます。 ### どこでも一貫したメトリクスを dbt Semantic Layer を使えば、メトリクスをひとつの場所で定義するだけ。ダッシュボード・プロダクト・レポートどこを見ても、常に同じ数字が表示されます。 ### アナリストが、データを自分の手で dbt があれば、エンジニアの対応を待たずに、アナリスト自身がデータの構築・テスト・管理をできます。 *** *コストを最適化する* ## スマートなオーケストレーションでコンピューティングコストを30%以上削減 Fusion により、プロダクションパイプラインがよりスマートになります。更新が必要なモデルだけを自動でビルドするため、複雑な設定や書き直しは不要。コンピュートの無駄を省きながら、SLAを維持し、プロジェクトを常に快適なスピードで動かし続けます。 [コスト削減について相談する](https://www.getdbt.com/jp/contact) *** ## 主要IDEに対応 使い慣れたIDEで、ネイティブなローカル開発環境を体験しましょう。Cursor・Claude Code・Windsurf・VS Code のIDE拡張機能に対応しています。 [Talk to a dbt expert ](https://www.getdbt.com/jp/contact) *** *実績が物語る、真の価値* ## 確かな成果を、目に見える形で 数千ものチームがdbtを採用し、データ品質と信頼性を向上させています。業務の効率化とコスト削減を同時に実現し、ビジネスの成長を強力に支えます。 ### データワークフローを加速 プロセスを自動化して、インサイトの提供を大幅にスピードアップします ### 6か月以内のROI Forrester Research社の調査結果によると、組織の成果創出を加速し、大幅なコスト削減と生産性向上を達成しています ### dbtの導入実績 あらゆる規模で、信頼できるデータ製品を安心して提供できます ### コンプライアンス対応 組み込み型のガバナンス、テスト、ドキュメント機能により、信頼できるデータを実現 *** *dbtが選ばれる理由* ## 世界中で信頼され、エンタープライズ規模で実証済み。 ### 80,000以上のチームがdbtを活用中 世界有数の企業において、信頼性の高い分析ワークフローと大規模なデータ活用を支えています。 ### G2で高評価を獲得 Gartner「DataOps Market Guide 2024」に掲載 ### 業界をリードするパートナーと連携 主要なデータプラットフォームやツールと連携。 ### 10万人以上のコミュニティメンバー ベストプラクティスを共有し、より良いデータプロダクトを共に構築する、世界最大級のオープンデータコミュニティです。 *** *dbt コミュニティ* ## データとAIの未来を共に作る、最大のコミュニティへ dbtコミュニティは、世界10万人以上のデータプロフェッショナルが集まる場所です。 みんなの知恵を借りて、もっと楽しく、もっとスマートに課題を解決していきませんか？ [コミュニティに参加する](https://www.getdbt.com/community/join-the-community) | [コミュニティについてもっと知る](https://www.getdbt.com/community) --- --- title: "dbt Labsについて" description: "dbt は、データアナリストやエンジニアがクラウドデータウェアハウスでデータを変換、テスト、文書化できるデータ変換ツールです。" url: "https://www.getdbt.com/jp/about-us" --- # 会社概要 dbt Labsのミッションは、データに関わるすべての人に力を与え、組織の「知恵」を生み出し、広めていく手助けをすることです - **80,000** dbtを利用している企業 - **5,700** dbt platformユーザー - **3,100** 認定アナリティクスエンジニア - **100,000** dbtコミュニティのメンバー *** ## リーダーシップチームのご紹介 ### Tristan Handy [object Object] ### Sarah Riley [object Object] ### Ryan Segar [object Object],[object Object],[object Object] ### Austin Stefani [object Object] ### Meg Pittman [object Object],[object Object],[object Object] ### Shawn Toldo [object Object],[object Object],[object Object] ### Seth Zelnick [object Object],[object Object],[object Object],[object Object] ### Drew Banin [object Object] ### Connor McArthur [object Object] *** ## 取締役会 ### Tristan Handy ### Connor McArthur ### Ashley Kramer ### Martin Casado ### Matt Miller *** ## dbt Labsをもっと知る 私たちのアイデンティティやプロダクト、そしてコミュニティがもたらす影響について、さらに詳しくご紹介します。 ### 最新ニュース dbt Labsに関する最新ニュースと、メディア掲載情報、プレスリリースをご覧ください。 [今すぐ読む](https://www.getdbt.com/press) ### dbtの導入事例を見る dbt platformを活用し、いかにして高品質で信頼性の高いデータを生み出しているのか、各組織の取り組みをご紹介します。 [導入事例にアクセス](https://www.getdbt.com/case-studies) ### dbt について 信頼できるデータをより迅速に。dbtがどのようにチームのデータ開発を加速させるのか、その仕組みをご紹介します。 [dbt について](https://www.getdbt.com/product/dbt) *** ## dbtで、データ開発を次のステージへ 開発から本番環境まで、データパイプラインの自動化と拡張をストレスフリーに。dbtが、ワークフローに変革をもたらします。 [dbtをもっと知る](https://www.getdbt.com/product/dbt) | [デモを予約する](https://www.getdbt.com/contact) --- --- title: "Blog Index Page" description: "dbt Labs ディスクリプション：アナリティクスエンジニアリングの最新トレンド、dbtの活用事例、業界インサイトをお届けします。" url: "https://www.getdbt.com/jp/blog" --- # Blog [グローバルサイトのブログを見る（英語）](https://www.getdbt.com/blog) | [グローバル dbt Developer ブログを見る　（英語）](https://docs.getdbt.com/blog) *** ### dbt Semantic Layer vs. Text-to-SQL：2026年ベンチマーク最新版 ### 2026年 アナリティクスエンジニアリング最新動向 ### 株式会社テレシー導入事例：AIとdbt platformで実現する 「AI-readyなデータ基盤」 --- --- title: "株式会社テレシー dbt 導入事例：AIとdbt platformで実現する 「AI-readyなデータ基盤」" url: "https://www.getdbt.com/jp/blog/case-study-telecy" --- # AIとdbt platformで実現する 「AI-readyなデータ基盤」 運用工数を実質ゼロ化し、リソースを事業成長と AIエージェント開発に集中投資 *** ![Image](https://cdn.sanity.io/images/wl0ndo6t/main/875709fdf6ce8aeb32efe1abe8022a50f9c4cf03-987x334.png) 会社名: 株式会社テレシー 事業: 運用型テレビCMを軸とした統合的なマーケティングコミュニケーション施策の企画・実行 *** *** - 開発生産性　20倍 - デバッグ時間削減　88％ - 運用保守工数　0 - 追加採用コストを削減　2名 *** *** ![Image](https://cdn.sanity.io/images/wl0ndo6t/main/18850a295e5e24d44233e04601ca3b5edaadeaba-1894x876.png) *** **事業成長と運用体制の間に生まれたギャップ **当初、Snowflakeとdbt Coreを組み合わせてデータ基盤を運用していましたが、事業の急速な成長に伴い、よりスピーディかつ堅牢なデータ開発体制が求められるようになりました。 - **開発スピードと品質保証の両立という課題**: 少人数体制の中、CI/CDの整備やモデルの依存関係に基づく自動テストの仕組みづくりに十分なリソースを割くことが難しく、リリース品質と開発速度を両立する仕組みの強化が必要でした。 - **自前運用によるリソース圧迫**: GitHub Actionsで構築したCI/CDの維持に、エンジニアが本来の開発業務とは別に週3〜4時間を費やしており、より付加価値の高い開発業務にリソースを振り向ける余地を生み出す必要がありました。 - **スケールに見合う体制構築の必要性**: 同等の品質を自前で維持し続けるには、少なくとも1〜2名の専任データエンジニアの追加採用が必要。事業スピードに見合った形で、いかに早く堅牢な体制を構築するかが論点となっていました。 *** **SaaSへの移行と「AI-ready」なデータ基盤設計** 「事業開発のスピード加速」を最優先とし、開発環境やCI/CDが標準で揃ったdbt platformへ移行。単なる効率化に留まらず、AI時代を見据えた基盤へと踏み込みました。 - **圧倒的な費用対効果**: 1〜2名のデータエンジニアを追加採用するコスト・時間と比較し、SaaSとして提供されるdbt platformの方がスピーディーかつ低コストで同等以上の体制を構築可能と判断。 - **AI-readyなデータモデリング**: dbtのYAMLファイルでメタデータ・テスト・依存関係を厳格に管理することで、データ開発にガバナンスと、自動テストが効く状態を担保。さらに、このYAML定義はAIにモデル生成を任せる際の強力なガードレールとしても機能します。AIが生成したSQLやモデルが、組織のルールから逸脱しないことを自動で検証できる土台となっています。 - **データ仕様の共通言語化**: dbt Docsによって、データモデルの依存関係や定義を開発者・利用者・AIエージェントが同じ視点で参照可能に。社内のデータ利活用とAI活用の双方を支える基盤になっています。 > > > — 欧陽氏 *** **運用工数「ゼロ」と、20倍の生産性向上** dbt platformへの移行は、開発スピードとデータ品質の両面に劇的な変化をもたらしました。 - **開発スピードの飛躍的な向上**: AIとdbtを組み合わせた開発スタイルにより、月8本のペースでデータモデルの新規開発ができる体制に。以前と比較して、生産性は20倍以上に向上したと実感しています。 - **運用工数の実質ゼロ化**:自前CI/CDのメンテナンスから解放され、週3~4時間を費やしていた運用工数が実質ゼロに。 - **トラブルシューティングの高速化**:以前は数十分かかっていたエラー対応やデバッグが、dbt platformのジョブ実行ログとアラート機能により、5分以内に短縮されました。 こうしたスピード面での効果に加え、dbtのテスト機能は、上流の「汚いデータ」に起因する異常を即座に検知し、誤った意思決定を防ぐ防波堤としても機能しています。 > > > — 吉濱氏 *** **「1人1台のAIエージェント」が活躍する世界線へ** 現在、マーケティング課題にAIを掛け合わせたライトニングシリーズの開発を進めており、データ基盤のさらに先の活用に向けた挑戦も始まっています。 - **データ開発を加速するAgentOpsの実現**: ユーザーインターフェースを通じて、裏側でデータモデルのビルドやテストが自動で回り、要件に沿ったマートが自動生成される 「Agenticな世界」へ挑戦していきます。 - **AIエージェントへの高品質データ供給**: 営業1人ひとりに専属のAIエージェントがつく未来に向け、会話型アナリティクスを支えるための独自の分析モデルと、正確で高品質なデータを供給し続ける基盤を強化していきます。 > > > — 吉濱氏 *** ## dbtの導入効果を今すぐ体験しませんか？ dbtのエキスパートが、dbt platformがどのように機能するのか、どのようにデータ分析戦略に貢献できるかをご説明します。 [デモを予約する](https://www.getdbt.com/jp/contact) | [無料アカウントを作る](https://www.getdbt.com/jp/signup) --- --- title: "dbt Semantic Layer vs. Text-to-SQL：2026年ベンチマーク最新版" description: "セマンティックレイヤーとText-to-SQLの違いを徹底比較。2026年のデータ活用において、どちらのアプローチがビジネスに適しているかを解説します。" url: "https://www.getdbt.com/jp/blog/semantic-layer-vs-text-to-sql-2026" --- # dbt Semantic Layer vs. Text-to-SQL：2026年ベンチマーク最新版 *** *読了時間の目安 11分* - Jason Ganz - Benoit Perigaud *** LLMを使ってデータから答えを得る方法は、大きく2つあります。モデルに直接SQLを生成させるか、dbt Semantic Layerのような構造化されたオントロジーを通じてクエリさせるか、です。どちらも実際のビジネス現場で成果を上げています。ただし、失敗の仕方はまったく異なります。どちらを選ぶかを判断するうえで本当に重要なのは、この違いを理解することです。 2023年に私たちは両アプローチを比較した[ベンチマークを実施し](https://roundup.getdbt.com/p/semantic-layer-as-the-data-interface)、Semantic Layerが大差で勝利しました。しかし2023年は、LLMの時間軸でいえば約1,000万年前に相当します。モデルのSQLを書く能力は劇的に向上しました。そこで、その差が縮まったかどうかを確かめるべく、最新世代のモデルでベンチマークを再実施しました。 ## TL;DR - **Text-to-SQLの精度は大幅に上がっています。**GPT-4世代から現在への改善は目覚ましいものがあります。 - **よくモデリングされたSemantic Layerの対応範囲内では、正答率が100%に近いかそれに達しています。**決定論的なクエリ生成により、LLMが微妙にずれた結果を出してしまうことがありません。 - **データモデリングの品質は、どちらのアプローチにとっても非常に重要です。** 生テーブルの上に最小限のモデリングを加えるだけで、結果は全体的に改善されました。 - **推奨：** アドホックな分析や小規模データセットにはText-to-SQL。精度が求められる大規模・複雑・整備されていないエンタープライズ用途にはSemantic Layerを推奨します。 数値は今後も改善し続けるでしょうが、根底にある原則は変わらないと考えています。ベンチマーク自体を試したい方、詳細なデータやコストを確認したい方は[リポジトリ](https://github.com/dbt-labs/dbt-llm-sl-bench)をご覧ください。それ以外の方は、方法論の詳細や学んだことについて、このまま読み進めてください。** ** ## 2つのアプローチの仕組み 本題の数値に入る前に、それぞれのアプローチの仕組みをおさらいしておきましょう。 **Text-to-SQL**はシンプルなアプローチです。LLMにスキーマ情報を渡し、自然言語の質問に答えるSQLクエリを生成させます。テーブル名・カラム名・関係性といった構造的な手がかりからデータのセマンティクスを推測し、毎回ゼロからクエリを組み立てます。データさえあればどんな質問にも対応できる柔軟性がある一方で、脆弱さも持ち合わせています。テーブルの結合を誤ったり、カラムの意味を誤解したり、実行はできても誤った結果を返すクエリを生成してしまうことがあります。質問と生成されたSQLの間には、何のガードレールもありません。 **dbt Semantic Layerのようなオントロジー駆動のアプローチ**は、まったく異なる方法で動作します。LLMに生のSQLを書かせるのではなく、ビジネスロジックを組み込んだ構造化されたオントロジー（メトリクス、ディメンション、エンティティ、およびそれらの関係性）をあらかじめ定義します。LLMの仕事は、自然言語の質問を適切なメトリクスとディメンションの組み合わせに落とし込むことだけです。実際のクエリ生成はMetricFlowが決定論的に行うため、LLMが誤った結合や不正確な集計を生み出すことはありません。正しいメトリクスとディメンションが選ばれれば、クエリの正確性は保証されます。さらに重要なのは、実行するたびに微妙に異なる「それらしい数値」が出てくることもないという点です。ロジックはコードとして定義されており、常に同じ結果を返します。ただしトレードオフもあります。対応できるのは、あらかじめモデリングされた範囲内の質問に限られます。 どちらにも存在価値があります。では、それぞれどこで力を発揮し、どこでつまずくのか？実際に検証しました。 ## ベンチマーク Juan Sequeda氏らがdata.worldで開発した[ACMEインシュアランスベンチマーク](https://github.com/datadotworld/cwd-benchmark-data)を使用しました。実世界の分析的な問題を模倣した、適度な複雑さを持つデータセットです。11の質問を複数のLLMで各20回実行しました。 テストした構成は4つです： 1. **Text-to-SQL**：エージェントがスキーマ情報をもとにゼロからクエリを作成 2. **最小限のdbt Semantic Layer**：元の（高度に正規化された）テーブルの上に構築した軽量なdbtプロジェクト 3. **モデリング済みdbt Semantic Layer**：dbtのベストプラクティスに沿って再構築したプロジェクト 4. **モデリング済みデータへのText-to-SQL**：ゼロからクエリを作成しますが、上記で作成した新しいモデルにアクセスできる状態 ![Image](https://cdn.sanity.io/images/wl0ndo6t/main/b53a36381503bf1cb986e1d1c8c2cb64eb81c442-1376x768.png) dbtユーザーにとって最も実態に近い比較は、モデリング済みプロジェクトでのText-to-SQL対Semantic Layerです。ひとつ注意点として、Text-to-SQLを機能させるためにスキーマ全体をコンテキストとして読み込みましたが、これは大規模なデータセットでは現実的ではありません。数値を読む際にはこの点を頭に置いてください。 ## どのモデルを使うべきか（思ったよりも差はない） フルベンチマークの前に、まずモデルの選択やReasoningレベルが結果に意味のある差をもたらすかどうかを確認しました。 Opus 4.6、Sonnet 4.6、GPT-5.3 Codex、GPT-5.2（GPT-5.4はAPI経由でまだ利用不可）を、複数のReasoningレベルでテストしました。Anthropicのモデルはlowからmax、OpenAIのモデルはnoneからxhighまでです。Semantic Layer経由で回答できる質問について、16通りの組み合わせの結果は以下のとおりです： 結論から言えば、Semantic Layerのクエリについてはほとんど関係ありません。ほとんどのモデルがReasoningの設定によらず100%かそれに近い正答率を達成しています。タスクが十分に具体的でコンテキストも明確なため、Reasoningトークンを増やしても効果が出ないのです。 Reasoningレベルを上げて変わるのは速度だけで、しかも遅くなる方向です。GPTモデルでxhighを使うと1クエリあたり平均20秒以上かかりましたが、highでは8秒で、精度の改善は見られませんでした。Anthropicのモデルでは、Reasoningレベルは結果にもレイテンシーにも影響しませんでした。 いくつかの想定外の結果もありました： - Sonnet 4.6がOpus 4.6を上回った（今回のユースケースでは） - GPT-5.3 CodexとGPT-5.2はほぼ同等の結果 - 大きいモデルが構造化データタスクに最適とは限らない これをふまえ、フルベンチマークはSonnet 4.6とGPT-5.3 Codexをデフォルトのレベルで実施しました。 ## 本題：2023年対2026年 LLMはデータに関する質問に、2年前より上手く答えられるようになっているのでしょうか？ **答えはYESです。** GPT-4（2023年11月）とGPT-5.3 Codex・Sonnet 4.6（2026年2月/3月）で、同じ11問を各20回実行して比較しました。2年前は一貫性のなかった問題も含め、両手法ともに100%正解できる問題が増えています。 以下は、MetricFlowにとってエンティティホップが多すぎるかどうかで分類した内訳です： 注目すべき点は以下のとおりです： - **Text-to-SQLの正答率がほぼ倍増し、32.7%から64.5%へ向上しました。** 大幅な改善です。 - **Sonnet 4.6とGPT-5.3 Codexは両手法でほぼ同じ結果でした：** SLの正答率は同一、Text-to-SQLの全体正答率も同一（どちらも64.5%）。 - **Semantic Layerの対応範囲内の問題については、両モデルとも100%正解しています。** 以前は、データは正しいのにモデルが期待するディメンションを選ばないという誤答が1〜2件発生することがありましたが、今はそれもなくなりました。 - **2023年にSemantic Layerで回答できなかった問題は、追加モデリングなしには今も回答できません。** ただし、ここに大きな違いがあります。**Semantic Layerは「回答できない」と明示します。誤ったデータを返すことはありません。** Text-to-SQLは平然と誤った数値を返します。 これが本番環境で最も重要な違いです。Text-to-SQLでは、失敗は「もっともらしいが誤った回答」として現れます。Semantic Layerでは、失敗は「エラーメッセージ」として現れます。 取締役会資料、監査対応、社内KPIダッシュボードなど、精度が問われる場面ではこの差が決定的です。 ## 少しモデリングを加えるとどうなるか 一部の問題がSemantic Layer経由で回答できなかったのは、元のスキーマが[第三正規形](https://en.wikipedia.org/wiki/Third_normal_form)で高度に正規化されており、[MetricFlow](https://docs.getdbt.com/docs/build/about-metricflow)には多すぎるエンティティホップが必要だったためです。そこでひとつの問いを立てました。このギャップを埋めるために、最低限どれだけのモデリングが必要なのか？ LLMに対して、11問すべてをSemantic Layer経由で回答できるようにするための最小限のdbtモデルを作成するよう指示しました。結果として、コードを一切書かずに、いくつかのテーブルを結合して対応するセマンティックモデルを含む[**3つの新しいモデル**](https://github.com/dbt-labs/semantic-layer-llm-benchmarking/commit/5dd5561)が作成されました。 変更をgitにプッシュするとSemantic Layerが自動的に更新され、ベンチマークを再実施しました。Text-to-SQLのテストでも、新しいテーブルと関係性を含むDDLコンテキストを更新しています。 結果は一目瞭然です。 たった3つのモデルを追加するだけで、Semantic Layerはベンチマークの全問に回答できるようになりました。また、Text-to-SQLの精度も向上し、**モデリングの改善が両方のアプローチに効果をもたらす**ことが改めて確認されました。 （GPT-5.2でも実施しましたが、結果は著しく弱く、Text-to-SQLの正答率はGPT-5.3 Codexの84.1%に対して68%にとどまりました。） ## **どちらを使うべきか** 答えはText-to-SQL対Semantic Layerという二択ではありません。用途に応じて両方を使うことです。 複数のテーブルが関わる場合（今回のベンチマークでは15テーブル）、Semantic Layerを使うことで決定論性が加わり、正答率が劇的に向上します。Semantic Layerが答えられる問題は正確に答え、答えられない場合はそう伝えます。誤ったデータを黙って返すことはありません。 Text-to-SQLはより柔軟で、データが存在する限りどんな質問にも対応できます。ただしその柔軟性には代償が伴います。もっともらしく、しかし誤った答えを返すことがあるのです。なお、生テーブルの上にモデリングを加えることで、両方のアプローチの精度が改善されました。 **私たちの考え方は以下のとおりです：** - **精度が重要な場面（取締役会資料、監査、OKR、KPI、週次レポートなど）：** Semantic Layerを設定し、LLMを接続する。 - **アドホックな探索（一度きりの質問、データディスカバリー、プロトタイピングなど）：** まずSemantic Layerで答えられるか試す。できなければ、軽微なモデリング変更でギャップを埋められるか検討する。それでも難しければ、できる限り多くのスキーマコンテキストを持たせてText-to-SQLで対応する。 ![Image](https://cdn.sanity.io/images/wl0ndo6t/main/7d6835fe6a1cef6f36ec0e4f6efdebdbe8c778cd-1376x768.png) これはまさに、[dbt agent skills](https://github.com/dbt-labs/dbt-agent-skills/blob/main/skills/dbt/skills/answering-natural-language-questions-with-dbt/SKILL.md)で推奨しているアプローチです。 ## 試してみる・データを詳しく見る フルベンチマークはオープンソースで、誰でも再現できます。元のノートブック+CSVの構成から、LLMとのやり取りに[Pydantic AI](https://ai.pydantic.dev/)、結果の保存にDuckDBを使ったPythonライブラリへと移行しました。 - **自分のデータでベンチマークを試す：** [dbt-labs/dbt-llm-sl-bench](https://github.com/dbt-labs/dbt-llm-sl-bench) - **コストとレイテンシーを確認する：** [フルベンチマークデータ](https://dbt-labs.github.io/dbt-llm-sl-bench/) - **独自のSemantic Layerをセットアップする：** [dbt agent skills](https://github.com/dbt-labs/dbt-agent-skills)を使ってAIに構築・設定してもらう - **質問や発見を共有する：** [dbt Community Slack](https://www.getdbt.com/community/join-the-community) の #tools-dbt-mcp へ --- --- title: "dbt アナリティクスエンジニアリング認定試験" description: "dbtを活用したデータモデリング・テスト・最適化のスキルを証明する認定試験。SQLの基礎知識とdbt実務経験6ヶ月以上の方に最適。オンラインで受験可能、合格後すぐに認定証を取得できます。" url: "https://www.getdbt.com/jp/certifications/analytics-engineer-certification-exam" --- # dbt アナリティクスエンジニアリング認定試験 アナリティクスエンジニアリング認定試験では、dbt を活用してアナリティクス基盤にエンジニアリングの原則を適用しながら、データモデルを構築・テスト・維持し、データを誰もが活用できる形にする能力を評価します。 [登録する](https://pages.talview.com/dbtlabs/certifications/) *** *対応バージョン：1.11* 試験時間 問題数 合格基準 受験料 *** ## 認定試験について 認定資格の取得は、専門知識を証明する重要なステップです。受験にあたっては、SQL の基礎知識と dbt または dbt Core の実務経験が 6 ヶ月以上あることを推奨します。この基礎知識があると、自信を持って試験に臨めます。 準備のために、試験ガイドでは[出題範囲](https://www.getdbt.com/certifications/analytics-engineer-certification-exam#faq)の詳細・[サンプル問題](https://www.getdbt.com/certifications/analytics-engineer-certification-exam#sample-questions)・[学習ガイド](https://www.getdbt.com/dbt-assets/certifications/dbt-certificate-study-guide-version-1-11)を提供しています。準備が整ったら、都合の良い日時で試験を予約してください。 [登録する](https://pages.talview.com/dbtlabs/certifications/) *** ## 出題範囲 ### dbt モデルの開発と最適化 - 生オブジェクトの依存関係の特定と確認 - dbt のコアマテリアライゼーションの理解 - モジュール化と DRY 原則の適用方法の理解 - ビジネスロジックをパフォーマンスの高い SQL クエリに変換する - `build`・`run`・`test`・`docs`・`show`・`snapshot`・`seed` などのコマンドの活用 - 論理的なモデルの流れの設計とクリーンな DAG の構築 - `dbt_project.yml` での設定の定義 - dbt パッケージの活用 - Python モデルの作成 - `grants` 設定を使ったユーザーへのモデルアクセス権の付与 - YAML でのスナップショットの作成 - データセットの特性に基づいた最適なインクリメンタル戦略の選択 - `--empty` フラグを使ったドライランでのモデルロジックとスキーマ定義の検証 - `--sample` フラグを使ったサンプルモードでのモデル実行 - マイクロバッチなど高度な dbt マテリアライゼーションの理解 ### dbt モデルのガバナンス管理 - モデルの形状を保証するためのコントラクトの追加 - モデルの新バージョンの作成と旧バージョンの廃止 - プラットフォームレベルでデータの整合性を担保するための YAML での制約の定義 ### データモデリングエラーのデバッグ - エラーメッセージのログの理解 - コンパイル済みコードを使ったトラブルシューティング - .yml コンパイルエラーのトラブルシューティング - 修正の開発・実装・マージ前のテスト - フラグを使った dbt の動作管理 ### dbt パイプラインのトラブルシューティングと最適化 - DAG における障害ポイントのトラブルシューティングと管理 - dbt clone の活用 ### dbt テストの実装 - 様々なモデルやソースに対するジェネリック・シンギュラー・カスタム・カスタムジェネリックテストの活用 - dbt モデルとソースの前提条件のテスト - ワークフローへの各種テストステップの実装 ### 外部依存関係の実装と管理 - dbt エクスポージャーの実装 - ソースの鮮度管理の実装 ### dbt ステートの活用 - ステートとステートセレクションの理解 - dbt retry の活用 *** ## サンプル問題 ### Questions 1 ### Questions 2 ### Questions 3 ### Questions 4 ### Questions 5 ### Questions 6 ### Questions 7 ### Questions 8 ### Questions 9 ### Questions 10 *** ## 認定資格を取得しよう dbt のスキルを証明して、認定資格を取得しましょう。 [登録する](https://pages.talview.com/dbtlabs/certifications/) --- --- title: "dbt アーキテクト認定試験" description: "安全でスケーラブルなdbt環境の設計スキルを証明する認定試験。環境管理・RBAC・dbt Mesh・ジョブ設定などを評価。オンラインで受験可能、合格後すぐに認定証を取得できます。" url: "https://www.getdbt.com/jp/certifications/dbt-architect-certification-exam" --- # dbt アーキテクト認定試験 dbt アーキテクト試験では、安全でスケーラブルな dbt 環境を設計する能力を評価します。環境のオーケストレーション・ロールベースのアクセス制御・他ツールとの連携・ベストプラクティスに沿ったチーム開発ワークフローに重点を置いた内容です。 [登録する](https://pages.talview.com/dbtlabs/certifications/) *** 試験時間 問題数 合格基準 受験料 *** ## 認定試験について 認定資格の取得は、専門知識を証明する重要なステップです。受験にあたっては、SQL の基礎知識と Enterprise dbt アカウントの管理経験が 6 ヶ月以上あることを推奨します。この基礎知識があると、自信を持って試験に臨めます。 準備のために、試験ガイドでは[出題範囲](#faq)の詳細・[サンプル問題](#sample-questions)・[学習ガイド](https://www.getdbt.com/dbt-assets/dbt-certificate-study-guide-for-cloud-architect)を提供しています。準備が整ったら、都合の良い日時で試験を予約してください。 [登録する](https://pages.talview.com/dbtlabs/certifications/) *** ## 出題範囲 ### dbt データウェアハウス接続の設定 - データウェアハウスへの接続方法 - IP ホワイトリストの設定 - プロジェクト接続の作成とテスト - IDE でデータにアクセスするための OAuth 認証 - OAuth 用のクライアント ID とシークレットの追加 ### dbt Git 接続の設定 - Git リポジトリと dbt の連携 - Git プロバイダーとのインテグレーション設定 ### dbt 環境の作成と管理 - 各環境へのアクセス制御の管理 - サービスアカウントを使用するタイミングの判断 - API を使ったキーペア認証のローテーション - 環境変数の理解と活用 - 新しい dbt デプロイ環境の作成 - 環境のデフォルトスキーマ／データセットの設定 - カスタムブランチの理解と環境への割り当て - 他の環境へのdeferral（参照委譲）の設定 - 本番環境／CI 実行用のウェアハウスアクセス認証情報の追加 ### ジョブ定義の作成と管理 - deferral を使った CI ジョブの設定 - dbt ジョブ内のステップの理解 - スケジュール実行の設定 - 実行コマンドの正しい順序での実装 - 新しい dbt ジョブの作成 - 環境変数の上書き・スレッド数・deferral・ターゲット名・dbt バージョン上書きなどのオプション設定 - プロジェクトのドキュメントサイトを生成するジョブの設定 - 他の dbt ジョブ完了後にトリガーされるジョブの設定（ジョブチェーン） - Advanced CI の設定 - セルフ deferral の設定 - deferral の種類と使い分けの理解 ### dbt のセキュリティとライセンスの設定 - API アクセス用サービストークンの作成 - 権限セットの割り当て - ライセンスマッピングの作成 - ユーザーの追加と削除 - dbt Enterprise 向け SSO アプリケーションの設定 - RBAC の作成と割り当て ### ジョブの監視とアラートの設定 - メール通知の設定 - Webhook を使った他システムとのイベント連携 ### dbt Mesh の構築とクロスプロジェクト参照の活用 - 追加の dbt プロジェクトの設定 - 環境タイプとクロスプロジェクト参照の関係の理解 - モデルガバナンスの活用 ### dbt Catalog の設定と活用 - dbt Catalog を使ったリネージの確認・問題のトラブルシューティング・コストとパフォーマンスの最適化 - dbt Catalog を使ったパブリックモデルとクロスプロジェクト参照の検索 *** ## サンプル問題 ### Question 1 ### Question 2 ### Question 3 ### Question 4 ### Question 5 ### Question 6 ### Question 7 ### Question 8 ### Question 9 ### Question 10 ### Question 11 *** ## 認定資格を取得しよう dbt のスキルを証明して、認定資格を取得しましょう。 [登録する](https://pages.talview.com/dbtlabs/certifications/) --- --- title: "dbtのエキスパートに相談" description: "dbt platformのライブデモを体験しませんか？専門スタッフがご質問にお答えし、データ品質の向上・開発効率化・AI活用の加速をどう実現できるかをご説明します" url: "https://www.getdbt.com/jp/contact" --- # dbtのエキスパートに相談 dbtのエキスパートがご質問に直接お答えします。dbt platformがどのように機能するのか、なぜ業界スタンダードなのか、どのようにお客様に貢献できるかを、ライブデモでご説明します。 - 開発をスピードアップ - データの品質と信頼を構築 - チーム連携 **データ業界トップクラスの信頼** *** ### dbtのアカウントを作成 dbtの無料アカウントで、信頼性の高いデータ製品の構築を迅速に開始しましょう。 [アカウントを作成する](https://www.getdbt.com/signup) ### 最適なプランを探す 料金プランを確認し、お客様、チーム、ニーズに最適なものを見つけましょう。 [料金を確認する](https://www.getdbt.com/pricing) ### サポートに問い合わせる dbtをご利用中のお客様は、いつでもサポートにお問い合わせいただけます。 [お問い合わせ](https://docs.getdbt.com/docs/dbt-cloud/cloud-dbt-cloud-support) --- --- title: "dbt認定資格" description: "dbt認定資格でアナリティクスエンジニアとしてのスキルを証明しましょう。アナリティクスエンジニアリング試験とアーキテクト試験の2種類を提供。オンライン受験可能、日本語対応。" url: "https://www.getdbt.com/jp/dbt-certifications" --- # データエンジニアとしての可能性を広げる、dbt認定資格 需要高まるアナリティクスエンジニアへ。 dbt認定資格でスキルを証明し、あなたの市場価値を最大化しよう。 [登録する](https://pages.talview.com/dbtlabs/certifications/) *** ## 認定資格を選ぶ あなたのスキルとキャリア目標に合った認定資格を選んでください。両試験ともオンラインで受験可能で、基本的な SQL の知識が必要です。dbt の使用経験が 6 ヶ月以上ある方に最適です。 dbt とアナリティクスエンジニアリングの認定資格で、スキルを証明しキャリアを加速させましょう。 #### dbt アナリティクスエンジニアリング認定試験 データモデルの構築・テスト・メンテナンスを通じて、データを誰もが活用できる形にする能力を証明します。 *日本語での受験も可能です。 #### dbt アーキテクト認定試験 プロジェクトの設定・トラブルシューティング・最適化、および dbt の接続環境の管理スキルを証明します。 *日本語での受験も可能です。 [登録する](https://pages.talview.com/dbtlabs/certifications/) *** ## スキルを証明して、キャリアを加速 dbt Labs チームメンバーによる審査でスキルを検証し、キャリアを前進させましょう。最近の[求人ボード](https://app.slack.com/client/T0VLPD22H/C7A7BARGT)をご覧になった方はご存知の通り、経験豊富なアナリティクスエンジニアへの需要は高まり続けています。 dbt 認定資格を取得すると： - 履歴書やソーシャルプロフィールでシェアできるデジタルバッジで、採用担当者や採用マネージャーに差をつけられます - dbt が信頼できるデータの業界標準であることを知る現在・将来の雇用主に、スキルを証明できます。 - データコミュニティでのネットワーキングやコラボレーションの場で、際立つ存在になれます。 [今すぐ登録する](https://pages.talview.com/dbtlabs/certifications/) *** ## FAQs ### 試験はどのように実施されますか？どこで申し込めますか？ 試験はオンラインで実施され、監視員による監督のもとで行われます。申し込みは[こちらからスケジュールを予約](https://pages.talview.com/dbtlabs/certifications/)してください。 ### 受験料はいくらですか？ オンライン監視試験の受験料は 200ドル USD です ### オンライン受験の環境要件は何ですか？ オンライン受験の詳細については、[システム要件とセットアップ手順](https://www.talview.com/en/test-taker-guide)をご確認ください。 ### 英語以外の言語で受験できますか？ はい、英語に加えて、dbt アーキテクト試験および dbt アナリティクスエンジニアリング認定試験は日本語でも受験できます。 また、dbt アーキテクト試験はフランス語でも受験可能です。 ### 試験はどのように採点されますか？ 試験は正答1問につき1点が与えられ、不正解は0点となります。すべての問題は均等に配点されています。 なお、各試験にはスコアに影響しない「非採点問題」が含まれています。これらは通常の問題と見分けがつかない形で出題されますが、回答はデータ収集・研究目的のみに使用され、合否には一切影響しません。 ### 間違えた問題を確認できますか？ 試験の公平性を保つため、スコアレポートに記載されている内容以上の情報はお伝えできません。 ### 最終スコアはパーセンテージで表示されますか？それとも点数ですか？ 試験終了直後に結果（合格・不合格）と、採点対象問題の正答率（パーセンテージ）が表示されます。問題数での表示ではありません。 ### 再受験のポリシーはどうなっていますか？ 試験に不合格だった場合、最後の受験から一定期間後に再受験を予約できます。再受験にも受験料 200ドル　（USD) が必要です。 ### キャンセルポリシーはどうなっていますか？ 試験のキャンセルまたは日程変更は、予約時間の24時間前までに Talview へご連絡いただければ無料で対応できます。24時間を切ってからのキャンセルの場合、受験料の返金はできません。 ### どのような問題が出題されますか？ 各試験には以下の形式の問題が含まれます： ・[多肢選択式](https://support.caveon.com/hc/en-us/articles/6177438689172-Multiple-Choice-Items-in-Scorpion-Explained) ・[穴埋め式](https://support.caveon.com/hc/en-us/articles/7272596297620-Fill-in-the-Blank-Items-in-Scorpion-Explained) ・[マッチング式](https://support.caveon.com/hc/en-us/articles/7110003867284-Matching-Items-in-Scorpion-Explained) ・[ホットスポット式](https://help.blackboard.com/Learn/Instructor/Original/Tests_Pools_Surveys/Question_Types/Hot_Spot_Questions) ・[順序並べ替え式](https://support.caveon.com/hc/en-us/articles/7110892165396-Build-List-Items-in-Scorpion-Explained) ・[択一選択式](https://domc.caveon.com/about)（DOMC） ### 結果はいつわかりますか？ 試験終了直後に、合格・不合格の結果が表示されます。 ### 合格するともらえるものは何ですか？ 合格者には以下が授与されます： ・[Accredible](https://accredible.com/) のデジタルバッジ（ソーシャルプロフィール・履歴書・個人または仕事用ウェブサイトに追加可能） ・印刷・額装用のデジタル証明書 ### 認定資格に有効期限はありますか？ dbt Labs のすべての認定資格は、取得日から2年間有効です。 ### オンライン監視に対応しているブラウザはどれですか？ Google Chrome・Microsoft Edge・Mozilla Firefox・Apple Safari に対応しています。[詳細はこちらをご覧ください。](https://support.caveon.com/hc/en-us/articles/360040429392-Supported-Web-Browsers-for-Caveon-Products) ### FAQ に記載されていない質問はどこで聞けますか？ 認定資格に関するご質問は、[certification@dbtlabs.com](mailto:certification@dbtlabs.com) までお気軽にお問い合わせください。 ### まとめて割引バウチャーを購入できますか？ まとめてバウチャーを購入される場合は、担当の営業アカウントマネージャーにご連絡ください。適用可能な割引についても対応いたします。 ### 試験はオープンブックですか？ 試験はオープンブックではありません。受験中はメモや参考資料の持ち込みは禁止されています。 ### 障がいのある受験者への配慮はありますか？ 配慮が必要な方は、[accessibility@dbtlabs.com](mailto:accessibility@dbtlabs.com) までメールにてご連絡ください。 *** ## 今すぐ試験を予約する パートナーである Talview を通じて試験を予約し、スキルを証明しましょう。オンラインで受験でき、合格直後に証明書を取得できます。 [登録はこちら](https://pages.talview.com/dbtlabs/certifications/) --- --- title: "dbt platform" description: "dbt platformは、データ変換・テスト・デプロイを一元管理するマネージドサービスです。チームの生産性を高め、信頼性の高いデータパイプラインを構築しましょう。" url: "https://www.getdbt.com/jp/dbt-platform" --- # AI Ready なデータ基盤の業界標準 AI-readyなデータが、アナリティクスを動かす。 [dbt アカウントを作る](https://www.getdbt.com/jp/signup) | [dbt エキスパートに相談する](https://www.getdbt.com/jp/contact) *** ## dbt とは？ dbt は、生データを信頼できるアウトプットに変換するフレームワークです。 データチームが SQL を書けば、テスト・ドキュメント・バージョン管理・デプロイは dbt がすべて処理します。 [dbt アカウントを作成する](https://www.getdbt.com/jp/signup) | [dbtについて詳しく知る](https://www.getdbt.com/jp/product/what-is-dbt) *** ## さまざまな先進的企業で選ばれるdbt - Thermo Fisher Scientific - Nasdaq - jetBlue - Virgin Media - Hubspot - Vestas *** ## dbt の機能 データチームが共通のフレームワークで構築・テスト・リリースできる環境を提供します。信頼できるデータを、より速く、より低コストで。やり直しのない開発を実現します。 ### プラン dbt Mesh で、分散したデータモデルを大規模に設計・管理。依存関係の定義、アクセスポリシーの適用、組織の成長に合わせたプロジェクト間の一貫性を維持します。 ### 開発 Studio IDE・VS Code拡張機能・dbt Canvasのいずれでも開発可能。Fusionのリアルタイム検証で、エラーを早期に発見できます。 ### デプロイ State Aware Orchestration が変更を検知し、必要な処理だけを自動で実行。 ウェアハウスの無駄なコストを省きながら、すべてのジョブを一か所で管理できます。 ### テストと監視 自動テスト・CI/CDパイプライン・リアルタイムのデータヘルス監視により、パイプラインの状態を完全に把握できます。問題がダッシュボードやAIの出力に影響する前に検知します。 ### ディスカバー カラムレベルのリネージを追跡し、モデルの依存関係を探索。dbt Catalog でアナリストがデータを見つけ、理解し、信頼できる環境を提供します。 ### 分析 dbt Semantic Layer でメトリクスを一元管理。ツールや用途を問わず、常に信頼できる数字をビジネス全体に届けます。 *** *次世代エンジン Fusion 搭載* ## 高速・高精度な SQL 処理で、データ開発を加速 Fusion はデータプラットフォーム全体で SQL の構文とセマンティクスを深く理解する SQL コンパイラです。 リアルタイムの IDE フィードバック・State-aware orchestration・AI エージェントが必要とする正確なプロジェクトコンテキストを提供するリッチなメタデータレイヤーを支えています。Rust と並列処理で構築された Fusion は、10,000 モデルのプロジェクトを dbt Core より最大 30 倍速く処理します。 ### より速く SQL をローカルでコンパイル — 数分かかっていたフィードバックループを数秒に短縮 ### コストを最適化 コードの変更やデータの更新状況を自動で追跡し、実行が不要なモデルをスキップすることで、無駄な処理を削減します。 ### AI ready なデータ基盤を強化 AI エージェントが正確に動作するために必要な、詳細なメタデータとデータの流れの情報を自動で生成します。 *** > > > — Ben Kramer *** ## 既存のツールとシームレスに連携 dbt はお客様のデータを保存しません。豊富な外部サービスとの連携とオープン標準への対応により、データをどこからでも必要な場所へ、安全に・柔軟にお届けします。 - Tableau - Fivetran - OpenAI - Snowflake - Azure AI - Databricks *** ## AI ready なデータは、dbt から dbt エキスパートに相談して、あなたのデータ環境への適合性を確認するか、今すぐ無料トライアルを始めましょう。 [デモを予約する](https://www.getdbt.com/jp/contact) | [無料トライアルはこちら](https://www.getdbt.com/jp/signup) --- --- title: "dbt Labs - Home" description: "dbtは、生データを整理・検証し、アナリティクス・ダッシュボード・AIが使える信頼できるデータに変換するプラットフォームです。世界8万チーム以上に選ばれ、データ品質の向上・コスト削減・AI活用を同時に実現します。" url: "https://www.getdbt.com/jp/home" --- # AI readyなデータ基盤が、ビジネスを動かす dbt は、生データを整理・検証し、アナリティクス・ダッシュボード・AIが使える信頼できるデータに変換するプラットフォームです。 [dbtのアカウントを作成する](https://www.getdbt.com/jp/signup) | [デモを予約する](https://www.getdbt.com/jp/contact) *** - phData - Nasdaq - Affirm - Omni - CHG Healthcare - Siemens - Infinite Lambda *** ### 新搭載の Fusion エンジンにより、dbt はデータチームのモデル構築を劇的に加速します。 ### ローカルでもクラウドでも。 *** *ビジネスに、真の変革を* ## スピード・信頼性・確かな結果、それが dbt が選ばれる理由です データの信頼性を高め、チームの生産性を最大化。dbt は、ビジネスの成長を支える強固なデータ基盤を構築します。 ### データ品質と信頼性を強化 豊富なメタデータが dbt Catalog とリネージを強化し、アナリティクスおよびAI開発のためのガバナンスと信頼できるデータを改善します。 ### 効率化とコスト削減 dbt を活用することで、無駄を省き、定型作業を自動化し、コストを削減しながらデータ提供のスピードを加速します。 ### 高品質なデータで、AIの精度を高める dbt はデータの信頼性・管理・ドキュメント化を徹底することで、AIが最高の品質のデータをもとに構築される環境を整えます。 ### 既存の業務を止めずに、データ基盤を最新化 dbt でパイプラインの構築・管理を標準化することで、普段の業務やデータに影響を与えることなく、レガシーツールから移行できます。 ### どこでも一貫したメトリクスを dbt Semantic Layer を使えば、メトリクスをひとつの場所で定義するだけ。ダッシュボード・プロダクト・レポートどこを見ても、常に同じ数字が表示されます。 ### アナリストが、データを自分の手で dbt があれば、エンジニアの対応を待たずに、アナリスト自身がデータの構築・テスト・管理をできます。 *** *コストを最適化する* ## スマートなオーケストレーションでコンピューティングコストを30%以上削減 Fusion により、プロダクションパイプラインがよりスマートになります。更新が必要なモデルだけを自動でビルドするため、複雑な設定や書き直しは不要。コンピュートの無駄を省きながら、SLAを維持し、プロジェクトを常に快適なスピードで動かし続けます。 [コスト削減について相談する](https://www.getdbt.com/jp/contact) *** ## 主要IDEに対応 使い慣れたIDEで、ネイティブなローカル開発環境を体験しましょう。Cursor・Claude Code・Windsurf・VS Code のIDE拡張機能に対応しています。 [Talk to a dbt expert ](https://www.getdbt.com/jp/contact) *** *実績が物語る、真の価値* ## 確かな成果を、目に見える形で 数千ものチームがdbtを採用し、データ品質と信頼性を向上させています。業務の効率化とコスト削減を同時に実現し、ビジネスの成長を強力に支えます。 ### データワークフローを加速 プロセスを自動化して、インサイトの提供を大幅にスピードアップします ### 6か月以内のROI Forrester Research社の調査結果によると、組織の成果創出を加速し、大幅なコスト削減と生産性向上を達成しています ### dbtの導入実績 あらゆる規模で、信頼できるデータ製品を安心して提供できます ### コンプライアンス対応 組み込み型のガバナンス、テスト、ドキュメント機能により、信頼できるデータを実現 *** *dbtが選ばれる理由* ## 世界中で信頼され、エンタープライズ規模で実証済み。 ### 80,000以上のチームがdbtを活用中 世界有数の企業において、信頼性の高い分析ワークフローと大規模なデータ活用を支えています。 ### G2で高評価を獲得 Gartner「DataOps Market Guide 2024」に掲載 ### 業界をリードするパートナーと連携 主要なデータプラットフォームやツールと連携。 ### 10万人以上のコミュニティメンバー ベストプラクティスを共有し、より良いデータプロダクトを共に構築する、世界最大級のオープンデータコミュニティです。 *** *dbt コミュニティ* ## データとAIの未来を共に作る、最大のコミュニティへ dbtコミュニティは、世界10万人以上のデータプロフェッショナルが集まる場所です。 みんなの知恵を借りて、もっと楽しく、もっとスマートに課題を解決していきませんか？ [コミュニティに参加する](https://www.getdbt.com/community/join-the-community) | [コミュニティについてもっと知る](https://www.getdbt.com/community) --- --- title: "モダンなデータ開発プロセス" description: "dbtは ELTプロセスにおけるデータ変換を効率化し、エラーを削減。 モダンなデータ開発環境で、チームの生産性を最大化します。" url: "https://www.getdbt.com/jp/modern-data-transformation" --- # 業界標準のモダンなデータ開発プロセス dbtは ELT（抽出、読み込み、変換）プロセスにおけるデータ変換を効率化し、エラーを削減。 モダンなデータ開発環境で、チームの生産性を最大化します。 Book a customized demo with a dbt expert and learn how your team can use dbt Cloud to produce reliable datasets, faster. Learn how dbt Cloud empowers your team to: **Develop faster** Deliver quality analytics faster with automation, modularity, and repeatability. **Build data quality and trust** Guarantee the reliability of business metrics with automated testing, documentation, and transparency. **Unite your team** Eliminate bottlenecks and silos with Python or SQL-driven development, so analysts and data engineers can transform data collaboratively. [デモを予約する](#demo) | [dbtについて学ぶ](#capabilities) *** ## さまざまな先進的企業で選ばれるdbt - Affirm - Nasdaq - Canva - Duolingo - TaskRabbit - GitLab - Hubspot - jetBlue - Air New Zealand - Thermo Fisher Scientific - Conde Nast - Vestas - Altis Consulting - Domain - New Relic - Anheuser-Busch Group - Hotelbeds - CHG Healthcare - Talkdesk - Virgin Media *** ## dbtとは？ dbtは、データウェアハウス（DWH）内の複雑な生データを、ビジネスに最適化された「信頼性の高いデータモデル」へと効率的に変換する、モダン・データトランスフォーメーションプラットフォームです。 従来のデータ開発は、複雑なSQLや属人化したスクリプトによりブラックボックス化し、開発サイクルの停滞を招いていました。dbtは、バージョン管理や自動テストといったソフトウェアエンジニアリングのベストプラクティスをデータ変換プロセスに導入。 ワークフローを標準化し、専門性を問わず誰もがデータ開発・分析に参加できる環境を提供することで、組織全体のデータ民主化と迅速な意思決定を実現します。 [デモを予約する](#demo) *** ## モダンなデータ開発プロセスがもたらす「5つの変化」 ### 共同開発の加速 共通言語や標準がないことによる属人化を解消します。 Git連携によるバージョン管理を標準化することで、複数人での開発やナレッジ共有を安全かつスムーズに行える環境を実現します。 ### プロセスの可視化 データリネージによりロジックの流れを自動ドキュメント化。 DWH内を100%可視化することで、変更履歴やデータフローの把握を容易にし、トラブル対応の工数を大幅に削減します。 ### 確実な再現性 宣言的SQLとデータモデリングのコードによる管理（IaC）で結果を統一。 環境に左右されず、いつでも同じ結果を確実に再現できる信頼性の高いデータ基盤を構築します。 ### 品質の仕組み化 dbt test + CI/CDで自動テスト、レビューを仕組み化し、品質を自動担保することで、バグや不整合が本番環境へ混入するリスクを最小限に抑えます。 ### 運用の最適化 必要な処理だけを高速に再ビルドする「SAO」で、運用を自動化・高速化。依存関係に基づき、更新が必要な箇所のみを効率的に実行することで、属人化を解消し、DWHコスト削減と開発スピード向上を両立します。 *** ## dbtのエキスパートに相談 dbtのエキスパートがご質問に直接お答えします。dbt platformがどのように機能するのか、なぜ業界スタンダードなのか、どのようにお客様に貢献できるかを、ライブデモでご説明します。 > > > — Luis Noguera, Yummy > > > — Ben Singleton, JetBlue > > > — Ramon Marrero, Dish Digital Solutions *** ## よくある質問 ### なぜdbtを導入すべきなのですか？ dbtは、ETL/ELTにおけるデータトランスフォーメーションのワークフローを効率化し、より効果的なデータパイプラインの管理を目指すデータエンジニアやアナリスト、データチームのために設計されています。特に、バージョン管理、ガバナンス、そして拡張可能なコラボレーションを必要としているチームに最適です。 ### dbt Core（オープンソース）と比較して、dbt platform（SaaS）を利用するメリットは何ですか？ dbt platformは、IDE環境でのデータテスト実行、ジョブスケジュール管理、統合されたドキュメント機能、専任チームによるサポートを提供します。さらに、GitHubやGitLabとのシームレスな連携などの機能を備えており、チーム全体でプロジェクトを効率的かつ安全に共同管理することをサポートします。 ### データのセキュリティはどのように担保されていますか？ dbtは、転送中および保存時のデータの暗号化、ロールベースのアクセス制御（RBAC）、MFA認証（多要素認証）など、業界をリードするセキュリティプラクティスを採用しています。エンタープライズレベルの安全なデータ開発環境を提供します。 ### 既存のデータウェアハウス（DWH）とどのように連携していますか？ dbtは、Snowflake、Databricks、BigQuery、Redshiftなどの主要なクラウド・データプラットフォームと連携しています。データを移動させることなく、データウェアハウス（DWH）上で直接変換処理を実行できるため、高い効率性とスケーラビリティを確保できます。 ### チームメンバーと共同で開発を行うことはできますか？ はい、可能です。dbtは、Git連携で複数のユーザーが同時にデータモデル開発を行えるコラボレーションソリューションを提供しています。バージョン管理、ドキュメント共有、ピアレビュー（相互レビュー）などの機能により、チーム全体で効果的なデータ開発をサポートします。 --- --- title: "Product - dbt" description: "ソフトウェアエンジニアリングの手法をデータ分析に取り入れ、いかなる複雑なデータの管理を可能にします。チームの能力を最大限に引き出す、dbt プラットフォームの構成要素をご紹介します。" url: "https://www.getdbt.com/jp/product/dbt" --- # 構造化データにおける AI の標準へ dbt で実現する、信頼性の高い「AI-ready」なデータ活用と分析の高速化。 [デモを予約する](https://www.getdbt.com/jp/contact) | [無料トライアル](https://www.getdbt.com/jp/signup) *** *dbtの活用シーン* ## データ活用のあり方を変える データのサイロ化を脱却し、拡張性の高いプラットフォームで分析ワークフローを一元化。あらゆるデータプラットフォームと連携し、生のデータを「AI-ready」なインサイトへと変換するための共通基盤を提供します。 *** [Watch video](https://youtu.be/N3ByqpVSGIM) *** ### プラットフォームコストの削減 ビジネスロジックを柔軟なプラットフォームに集約。コードの記述と実行を効率化し、データプラットフォームへの投資を最適化します。 ### デリバリーの加速 ワークフローのあらゆる工程に組み込まれた AI で、生産性を劇的に向上。ボトルネックを解消し、データリテラシーを高めながら、ガバナンスの効いたセルフサービスを促進します。 ### データへの信頼性を確立 ガバナンスとオブザーバビリティが確保されたデータを、スピードを損なうことなく、データライフサイクル全体にわたって品質、一貫性、そしてコスト効率を担保します。 *** *スケーラブルなワークフロー* ## Analytics Development Lifecycle (ADLC) 成熟したデータチームが、優れたアイデアを形にし、ガバナンスを効かせながら拡張していくための最適解、それがADLCです。計画立案から運用監視に至るまで、dbtは全工程に最適化された機能を提供し、チームの歩みを止めません。 [ADLCについて詳しく知る](https://www.getdbt.com/resources/guides/the-analytics-development-lifecycle) *** *dbt features* ## 分析ワークフローを包括するプラットフォーム・エクスペリエンス ソフトウェアエンジニアリングの手法をデータ分析に取り入れ、いかなる複雑なデータの管理を可能にします。チームの能力を最大限に引き出す、dbt プラットフォームの構成要素をご紹介します。 ### データ変換 SQL を書くだけでデータモデルを構築。バージョン管理と CI/CD でパイプラインを常に正常に管理。 ### オーケストレーション エンドツーエンドのパイプラインを自動化し、確実にコードをデプロイ。 [Learn more](https://www.getdbt.com/product/deploy) ### オブザーバビリティ プロアクティブなテストとモニタリングにより、問題を迅速に解決しデータの健全性を維持。 ### カタログ 包括的なリネージを可視化。メタデータを深掘りしてコンテキストを把握し、データ製品の質を向上。 ### セマンティックレイヤー 一貫したメトリクスを定義し、様々なダッシュボードや LLM に連携。 ### メッシュ メッシュアーキテクチャにより、組織横断・プラットフォーム横断の複雑な環境を最適化 *** *次世代エンジン* ## Fusion：dbtを支える次世代エンジン 新世代の超高速エンジンが誕生。 スピード、開発体験、コスト効率をすべて次のレベルへ。 [Explore Fusion](https://www.getdbt.com/product/fusion) *** *成果につなげる* ## 業界標準を、自社の標準へ。 dbtを導入することで、データ品質をデータ／AI開発の基盤として確立できます。 共通の仕組みでチームが連携し、無駄なコストを増やすことなく、効率よくビジネス成果を実現します。 ### データ品質と信頼性を向上 組み込みテストで問題を事前に検知し、自動化によってパイプラインを安定運用。 データの状態をチーム全体で可視化・共有できます。 ### コンテキストを統合 データウェアハウス、ツール、チーム間のサイロを解消。 メタデータを“つなぐ基盤”として、共通基盤のもとでコラボレーションを実現します。 ### スケーラブルなコラボレーションを実現 直感的なインターフェースと適切なガバナンスにより、より多くの関係者が安心してデータ活用に参加できます。すべては統合された共通基盤の上で実現します。 *** ## 信頼できるデータを迅速に 単一のモデルからデータメッシュまで。 dbtは、モダンなデータチームが信頼できるデータを継続的に提供し、組織全体へ拡張するためのプラットフォームです。 [デモを予約する](https://www.getdbt.com/jp/contact) *** ## データスタック全体に - BigQuery - Databricks - Fabric - Fivetran - Redshift - Snowflake *** *dbtが選ばれる理由* ## 世界中で信頼され、エンタープライズ規模で実証済み。 ### 80,000以上のチームがdbtを活用 世界有数の企業において、信頼性の高い分析ワークフローと大規模なデータ活用を支えています。 ### G2で高評価を獲得 Gartner「DataOps Market Guide 2024」に掲載 ### 業界をリードするパートナーと連携 主要なデータプラットフォームやツールと連携。 ### 10万人以上のコミュニティメンバー ベストプラクティスを共有し、より良いデータプロダクトを共に構築する、世界最大級のオープンデータコミュニティです。 *** *最初の一歩へ* ## 信頼性を高め、スピードを加速し、コストを最適化。 dbtは、信頼できるスケーラブルなデータ活用を実現するためのチームの中核基盤です。 [デモを予約する](https://www.getdbt.com/jp/contact) | [無料アカウントを作成する](https://www.getdbt.com/jp/signup) --- --- title: "dbtとは" description: "dbtは、ソフトウェアエンジニアリングのベストプラクティスをデータ変換に取り入れ、信頼性の高いデータプロダクトを構築できるツールです。自動テスト・バージョン管理・ドキュメント化により、データチームの開発効率を最大化します。" url: "https://www.getdbt.com/jp/product/what-is-dbt" --- # 業界標準のモダンなデータ開発プロセス dbtは、ソフトウェアエンジニアリングのベストプラクティスを分析業務に取り入れることで、データ活用を「共有可能で、拡張性のある取り組み」へと進化させます。 [無料トライアル](https://www.getdbt.com/jp/signup) | [デモを予約する ](https://www.getdbt.com/jp/contact) *** *dbtが選ばれる理由* ## 生データを、信頼できるデータプロダクトへ 分析・業務からAI活用までを支える、保守性の高いデータプロダクトを構築できます。 ### クラウド環境に最適 データを移動・複製することなく、クラウド上でそのままデータ変換が可能です。 ### モジュール設計 処理を小さく分けて管理できるため、修正や再利用が簡単です。 ### チームで効率的な共同開発 定義を一元管理し、チーム全体で安全かつスムーズに開発できる環境を実現します。 *** ## データ変換にエンジニアリングのベストプラクティスを dbtは、自動テスト・バージョン管理・ドキュメント化などの ソフトウェア開発の手法をデータ変換プロセスに取り入れています。 これにより、データチームは安心して開発を進めることができます。 ### コードでデータ変換を定義 ビジネスロジックを反映したSQL（SELECT文）を記述することで、 保守・運用しやすいデータモデルを構築できます。 ![Diagram showing a dbt model definition using a ref function to query the stg_jaffle_shop_customers model, transforming customer data for use in product_analytics.](https://cdn.sanity.io/images/wl0ndo6t/main/71926d421915cec51ed893e8bf1eedf27d2e4b06-1224x1224.png) ### 開発と同時にテスト テストを作成・実行することで異常を早期に検知し、正確で信頼できるデータモデルを維持できます。 ![Image showing a dbt test configuration for the customer_id column in the stg_jaffle_shop_customers model, validating uniqueness and non-null constraints using the dbt test command.](https://cdn.sanity.io/images/wl0ndo6t/main/2ec07ec67cc0939aa8debde07c831022b9bef2ee-1224x1224.png) ### ドキュメント化して共有 モデルやカラムに説明・タグ・管理者情報を付与し、自動生成されるドキュメントから簡単に検索できます。 ![Screenshot of a dbt model detail view for dim_customers_v3, showing description, unique ID link, project name, and exposure type metadata within dbt Cloud.](https://cdn.sanity.io/images/wl0ndo6t/main/dc1054cdda25b4d72769370e0a95c9813e3e3d88-1224x1224.png) ### ロジックをバージョン管理 Gitを使ってすべての変更履歴を管理し、レビューや変更内容の追跡、データロジックの可視化を実現します。 ![GitHub pull request view in dbt Cloud, showing model-level changes with indicators for modified, added, and removed rows, plus a 4% row difference warning before merging.](https://cdn.sanity.io/images/wl0ndo6t/main/3654ae10d306cb4ea06dcd9c3b29017ed9ea9124-1224x1224.png) *** ## dbtで、データ活用を次のステージへ コラボレーション、テスト、デプロイ、拡張まで、 分析ワークフローをより速く、効率的に実現できます。 [無料トライアル](https://www.getdbt.com/jp/signup) | [デモを予約する](https://www.getdbt.com/jp/contact) *** ## さまざまな先進的企業で選ばれるdbt - Thermo Fisher Scientific - Nasdaq - jetBlue - Anheuser-Busch Group - Virgin Media - Hubspot - Conde Nast - Vestas *** > > > — James Densmore氏 > > > — Benjamin Singleton氏 > > > — Rebecca Funk氏 *** ## 主要なデータスタックに幅広く対応 - BigQuery - Databricks - Fabric - Fivetran - Redshift - Snowflake *** ## 導入企業に学ぶdbtの活用事例 さまざまな業界の企業が、dbtを活用して、データ変換をより迅速に、低コストで、確実に実現している事例をご紹介します。 ### 金融サービス：リスク管理と不正検知の自動化 金融サービス業界では、リスク管理と不正検知が最優先課題です。 銀行は膨大な取引データを扱いながら、規制への対応を維持しつつ、潜在的な不正行為を早期に検知する必要があります。 dbtを活用した、主な取り組み内容： - 取引データを活用し、異常な支出パターンを検知して、不審な取引を特定するデータモデルを構築 - 不正の可能性を正確に検知するためのテストを実施し、誤検知や見逃しを削減 - データの変換・検証プロセスを明確にドキュメント化し、コンプライアンス部門と連携して内部統制および規制要件への対応を強化 **成果**：dbtの導入により、銀行はリスク管理プロセスの主要部分を自動化し、コンプライアンス対応にかかる手作業を削減するとともに、不正リスクの未然防止を実現。 **dbt Cloudを活用している金融サービスのお客様：** ### ヘルスケア：患者データの最適化によるケアとレポートの改善 ヘルスケア分野では、診察記録、検査結果、処方情報などの患者データを、 医療従事者や管理者にとって価値あるインサイトへと変換することが求められています。 大規模な医療ネットワークでは、患者の治療成果・回復状況の標準化や、コンプライアンス対応の強化が重要な課題となっています。 dbtを活用した、主な取り組み内容： - 複数の電子カルテ（EHR）システムの患者データを統合し、分析しやすい単一のデータ基盤を構築 - 検査結果や処方データを、治療成果を可視化するモデルに変換し、医師によるデータに基づいた意思決定を支援 - データテストを自動化し、機密性の高い患者データの正確性を確保するとともに、臨床研究やアウトカム分析における報告ミスのリスクを低減 - 監査対応可能なドキュメントを整備し、すべてのデータ変換プロセスが医療基準・規制要件を満たすよう管理 **成果：**dbtで患者データの一元化とクリーニングを行うことで、医療提供者はより迅速で正確な意思決定ができるようになり、患者アウトカムの向上とレポート業務の効率化を実現。 **dbtを活用しているヘルスケアのお客様：** ### eコマース：商品おすすめ機能とマーケティングキャンペーンの最適化 Eコマース分野では、顧客行動を正しく理解することが、 商品おすすめ機能のパーソナライズや、効果的なマーケティング施策の実施において重要な役割を果たします。 オンライン小売業者は、購買履歴、Webトラフィック、ユーザー嗜好データを活用し、商品おすすめエンジンの高度化を目指しています。 dbtを活用した、主な取り組み内容： - クリックストリームや販売データを分析し、顧客の購買傾向を可視化するデータモデルを構築 - 自動テストによってデータの正確性を確保し、偏ったデータがレコメンデーションに影響するリスクを低減 - 商品アフィニティモデルを構築し、嗜好に基づく顧客セグメントを作成して、パーソナライズされた施策を展開 - データパイプライン全体をドキュメント化し、マーケティングチームがデータの生成プロセスを理解しやすい環境を整備 **成果**：dbtの活用により、小売業者はリアルタイムデータをもとに商品おすすめ機能を柔軟に最適化できるようになり、パーソナライズ施策による売上拡大と顧客離れの防止を実現。 **dbtを活用しているeコマースのお客様：** ### 製造現場の自動化分野：生産ラインの効率化と予知保全の高度化 製造現場の自動化分野では、生産ラインのパフォーマンス最適化や、予知保全によるダウンタイムの削減が重要な課題となっています。多くの企業は、複数の工場に設置されたIoTデバイスやセンサー、機械ログから大量のデータを収集していますが、それらを実用的なインサイトへと活用することに課題を抱えています。 dbtを活用した、主な取り組み内容： - 生産ラインのセンサーデータを活用し、稼働率、生産速度、エネルギー使用量などの主要指標（KPI）を可視化するデータモデルを構築 - 機械の稼働履歴や故障履歴をもとに予知保全モデルを統合し、故障の兆候を早期に検知して、計画的な保全対応を実現 - 自動テストによって変換データの正確性・信頼性を確保し、誤った予測による生産計画への影響を防止 - データ変換プロセスや予測モデルの構築内容をドキュメント化し、現場の管理者やエンジニアがリアルタイムで活用できる環境を整備 **成果**：dbtの活用により、企業は計画外停止の削減やエネルギー効率の改善を実現し、生産性の向上とともに、信頼性の高いデータに基づく早期対応によって、メンテナンスコストの最適化を達成。 **dbtを活用している製造現場の自動化分野のお客様：** --- --- title: "登録" description: "個人開発者は永久無料、チームは14日間無料トライアルでdbt platformをお試しいただけます。すぐにセットアップして、信頼性の高いデータパイプラインの構築を始めましょう。" url: "https://www.getdbt.com/jp/signup" --- # dbtのアカウントを作成する dbtのアカウントは、個人開発者であれば永久に無料です。チームでの利用も14日間無料トライアルでお試しいただけます。大規模・複雑なプロジェクトの場合は、[dbtのエキスパートにご相談](https://www.getdbt.com/jp/contact/)ください。 - すぐにセットアップ - 直感的なUI - チームで試せる **多くの先進企業に選ばれています。** --- --- title: "2026年 アナリティクスエンジニアリング最新動向" description: "2026年のアナリティクスエンジニアリングの最新動向を網羅したレポート。業界のトレンド、ツール、キャリアパスを詳しく解説します" url: "https://www.getdbt.com/jp/state-of-analytics-engineering-2026" --- # 2026年 アナリティクスエンジニアリング最新動向 本レポートは、dbt Labsが発行した『2026年 アナリティクスエンジニアリング最新動向』の要約版です。完全版（英語）をご覧になりたい方はこちらからダウンロードいただけます。 [完全版（英語）をダウンロードする](https://www.getdbt.com/resources/state-of-analytics-engineering-2026#download-report) | [レポート深掘りウェビナーに参加する](https://www.getdbt.com/resources/webinars/2026-state-of-analytics-engineering-virtual-event-japan) *** ## アナリティクスエンジニアリングの加速 アナリティクスエンジニアリングは、転換点を迎えました。人工知能はもはや「実験的な技術」ではありません——今や予算が組まれ、チームに根付き、日々のワークフローの中核を担っています。 コードの生み出し方、インサイトの届け方、インフラへの投資判断まで、あらゆる場面でAIの影響が及んでいます。かつて「試行錯誤」だったものが、今では「当たり前」になりました。 2026年、この分野を定義するのはAIがもたらす加速と、それが生み出すプレッシャーです。しかし同時に、データ品質・オーナーシップの明確化・ガバナンス規律といった、アナリティクスエンジニアリングが長年抱えてきた課題は、依然として解決されていません。 AIはアナリティクスチームの可能性を広げています。しかしその成果の信頼性を支えるのは、バリデーション・明確なオーナーシップ・強固なデータ管理という「仕組み」です。 2026年のレポートが示す現実：AIはアウトプットを加速させている。 しかし、それを支える信頼とガバナンスの整備は、追いついていない。 そして2026年のテーマは 「データチームは、品質と信頼を守りながら、スピードと生産性への期待に応え続けられるのか」です。 *** ### 主な調査結果 - コーディングのAI活用が当たり前に - 「信頼」と「スピード」が、新たな成功指標へ - ガバナンスへの懸念は、依然として高水準 - インフラコストが、予算の伸びを追い越している *** #### 2025年→2026年：何が変わったか 2025年から2026年への変化は、拡大よりも「定着」です。昨年急加速したものが、今や日常のワークフローとして根付いています。 この移行を定義する3つのパターンがあります。: **1. 加速 → 統合** AIを活用したコーディングは急速な採用フェーズを終え、今や標準的なワークフローとして定着。 **2. 実現 → 信頼性** アクセスの拡大から信頼性の強化へ。あいまいなオーナーシップなどの構造的課題は残るものの、信頼が明確な戦略的優先事項へ。 **3. スピード vs コスト → スピード vs 信頼** フォーマンスの定義が変わった。「いかに効率よく」から「速く動きながら、いかに信頼を維持するか」へ。 ##### 2025年は可能性。2026年は規律。 2026年版レポートは、AIがもたらす持続的な加速の中でデータチームがどのように動いているかを探ります。優先事項がどこで変化し、制約がどこに残り、そのシグナルがアナリティクスエンジニアリングの次のフェーズについて何を示しているか。その実態を捉えます。 *** ## ハイライト #### AI採用がアナリティクスエンジニアリングを再形成している **本レポートにおけるAIの定義** 本レポートでは、AIの活用を2つに分けて定義しています。 **AIを活用したコーディング：**実務担当者がアナリティクスコード（SQL、Python、YAML）、テスト、ドキュメントの作成・リファクタリングに使用するLLM。 **AI生成インサイト：** 自然言語プロンプトから生成される、ステークホルダー向けのアウトプット。 セクションの見出しで「AI」と表記する場合は両方を指し、分析セクションでは該当するレイヤーを明記しています。 #### AIがアナリティクスワークフローに定着している AIはもはやアナリティクスチームの「実験」ではなく、日常業務に組み込まれています。 72%がAIを活用したコーディングを開発プロセスの優先事項とし、リーダー層では77%以上が生産性向上のためにAIを重視しています。 ![Image](https://cdn.sanity.io/images/wl0ndo6t/main/bc137c1d01a17406c99754b7947f2614db1244ab-1112x584.png) LLMの活用は今やアナリティクス開発ワークフローに組み込まれており、主にドラフトから本番までのサイクルタイムを短縮しています。 AIを活用したコーディングは戦略的な重点領域となっていますが、パイプライン全体への投資は依然として不均一です。 **72%がAIを活用したコーディングを優先する一方、テスト・オブザーバビリティ・品質管理を含むパイプライン管理へのAI活用を優先するのはわずか24%にとどまります。**チームはAIで「作る速度」を上げていますが、「守る仕組み」は同じペースで強化されていません。 これはコーディングとパイプライン作業の違いではありません。AIを活用したコーディングは、パイプライン開発の方向性にも影響を与えています。 この対比の本質は「加速」と「安定化」の差です： - **加速**：モデル・変換・ドキュメントをより速く生成する - **安定化**：パイプライン内のバリデーション・テスト・オブザーバビリティ・ガバナンスを強化する 現在、AIへの投資は安定化より加速に傾いています。 > > > — Kasey Mazza, Hubspot #### ガバナンスへのプレッシャーが高まっている AI採用が拡大するにつれ、ガバナンスへの備えが重要な課題として浮上しています。本セクションのデータが示すのは、加速するAI導入と、そのアウトプットを検証・管理するための仕組みとの間に、じわじわと広がるギャップです。 AIがアナリティクスチームのアウトプット量を増やすほど、懸念もその勢いに比例して膨らんでいます。2026年のガバナンスが直面する核心的な問い——バリデーション・テスト・監視の仕組みは、AI主導のアウトプットと同じスピードで成熟しているのか。 > > > — Bruno Lima, phData #### リスク認識は依然として高水準 AI採用が進むにつれ、それに伴うリスクへの認識も高まっています。 回答者の71%がハルシネーションや不正確なデータがステークホルダーに届くことを懸念しており、その強度は役割によって異なります。 ![Image](https://cdn.sanity.io/images/wl0ndo6t/main/6ed1440bad8915dee2a8be22e07ed0c3fe8d78a2-1112x876.png) 実務担当者はリーダーよりも実装リスクを身近に感じており、LLMへの機密データの露出についてリーダーより7ポイント高い懸念を示しています。また、AIを活用した開発が品質に与える影響についても高い懸念を示しています。一方リーダーは、コンプライアンス・ドキュメント・ガバナンス準備の観点から課題を捉える傾向があります。 このパターンが示すのは、距離感の違いです。実務担当者は実行リスクを直接体験し、リーダーはガバナンス責任を構造的に捉えています。 AIの採用は2つの面で加速しています。AIを活用したコーディングによる開発スピードの向上と、AI生成インサイトによるステークホルダー向けアウトプットの拡大です。しかし、バリデーション・テスト・ガバナンスへの投資は同じペースで増えていません。 ![Image](https://cdn.sanity.io/images/wl0ndo6t/main/ea89e37d5b7afc307b779a91432ee82082969e34-1112x798.png) アンバランスは明白です。AIを活用したコーディングの優先度など、AI加速の主要指標は70〜80%の範囲にあり、信頼も同様の戦略的重要性（83%）を持っています。一方、ガバナンス投資と基盤的なデータ課題は依然として不均一なままです。 **アウトプットのスケールが、安定化のスピードを上回っています。** > > > — James Waller, Lendable #### このことが意味するもの アナリティクスワークフロー全体でのLLM活用は、実験から実装へと移行しました。今日のAIの主な影響は業務上のもの——ドラフトから本番までのサイクルタイムを短縮し、コードや分析を速く届ける支援をしています。 AIは2つの次元でスケールしています。エンジニアリングAIを活用したコーディングによる開発スピードの向上の向上と、ステークホルダー向けアウトプットの拡大です。しかし、バリデーション・テスト・ガバナンスへの投資は同じペースで増えていません。デリバリーのスピードが上がり、AI生成インサイトがより多くのステークホルダーに届くにつれて、それを守るコントロールの成熟は遅れています。 **安定化なき加速は、リスクを複利で増やすだけ。** > > > — Bruno Lima, phData ## 「信頼」と「スピード」が最重要指標へ アナリティクスチームへのパフォーマンス期待が変わりつつあります。2026年、コストへのプレッシャーが残る中でも、信頼とスピードが最も重視される優先事項となっています。 データとデータチームへの信頼を重要とする割合は2025年の66%から83%へ、スピードは50%から71%へと急上昇。コスト削減は48%から53%とわずかな伸びにとどまりました。 信頼とスピードの重要性は他のどの指標よりも速く高まっており、単なるアウトプットではなく、速く届けられる信頼できるアウトプットへ、アナリティクスのパフォーマンスの定義が変化していることを示しています。 ![Image](https://cdn.sanity.io/images/wl0ndo6t/main/22c23e541c23e04ecbb8fdbc4fe2013e05a475a7-1112x584.png) 2026年における「重要」「非常に重要」の回答の集中は、この変化を裏付けています。信頼は今や全指標の中で最も高い優先度を持ち、その前年比の伸びはスピードやコストよりも顕著です。 ![Image](https://cdn.sanity.io/images/wl0ndo6t/main/be74a4b4d1533e9cd32a663e569d075e958aaf8b-1112x584.png) アナリティクスチームはかつて主にアウトプット量と効率で評価されていました。2026年、それだけでは足りません。AIを活用したコーディングとAI生成インサイトが届けるスピードと規模が増す中、求められるのは「速いインサイト」ではなく「ステークホルダーが頼れる速いインサイト」です。 コスト規律は依然として重要ですが、もはや最優先のパフォーマンス指標ではありません。スピードだけでは不十分で、組織はより速いデリバリーと結果への高い信頼を同時に求めています。この文脈において、成熟度とは加速下での信頼性。「精度・一貫性・信頼を維持しながら速く動く能力」によって定義されます。 #### このことが意味するもの スピードとコストは依然として重要ですが、信頼が今や両方の土台となっています。AI生成インサイトがステークホルダーに届くようになるにつれ、信頼性はアナリティクスのパフォーマンスを測る基準の一部となっています。組織はもはやアウトプットや効率を最優先に最適化するのではなく、スピードを保ちながらステークホルダーが頼れるインサイトを届けることを求められています。 > > > — Pooja Crahen, Okta ## 統合は改善、しかし信頼の課題は続く アナリティクスエンジニアリングのすべての課題が同じ方向に動いているわけではありません。運用上の摩擦は一部緩和されていますが、構造的な制約は残っています。 **「様々なソースからのデータ統合」を主要課題として挙げる割合は、2025年の35%から2026年の27%に低下しました。**かつて定義的な痛点だった技術的統合は、多くのチームにとって対処しやすくなってきています。 ![Image](https://cdn.sanity.io/images/wl0ndo6t/main/c4522b0f125909cd046e0eb40a3b7ef1f8d2b801-1112x584.png) 一方、他のシグナルは驚くほど一貫しています。データオーナーシップのあいまいさは依然として41%の課題であり、前年からほぼ変化がありません。データ品質の低さは組織全体で最も頻繁に報告される障壁であり続けています。 ステークホルダーのデータリテラシー不足は36%の回答者にとって障壁であり、昨年の39%からわずかに低下。信頼のギャップが技術システムを超えて組織のダイナミクスにまで及んでいることを示しています。 統合の課題は減少していますが、オーナーシップ・品質・リテラシーの制約は続いており、ボトルネックはインフラから責任へとシフトしています。 これらの課題に対する認識は役割によっても異なります。 ![Image](https://cdn.sanity.io/images/wl0ndo6t/main/497ffb58e65d0f521cb4c05e9016cd922edf62a0-1112x930.png) ほとんどの課題認識は役割間で概ね一致していますが、日々の責任と監督の違いを反映して、一部の領域では差異が生じています。 注目すべきは、「ステークホルダーからのデータへの信頼不足」を主要課題として挙げるチームが減少（33%→24%）している一方で、信頼が戦略的優先事項として急上昇していることです。 ![Image](https://cdn.sanity.io/images/wl0ndo6t/main/72a7bf5aac49357cbb9b18b169f850ecc4ce8a6a-1112x584.png) #### このことが意味するもの 技術的統合の改善は、より深い信頼の制約を解消していません。信頼を個別の運用上の問題として捉えるチームは減った一方で、戦略的な期待として捉えるチームが増えており、孤立した摩擦から構造的な責任へのシフトを示しています。 品質の維持・オーナーシップの明確化・ステークホルダーの整合という作業はなくなったわけではなく、基盤として定着しています。加速が増し信頼への期待が高まるにつれ、解決されていない品質・オーナーシップ・リテラシーのギャップはより大きな影響を持ちます。 アナリティクスエンジニアリングは実現する役割から管理する役割へと進化しており、インテリジェントシステムが単に速くではなく、信頼性を持ってスケールすることを確かにする責任を担っています。 > > > — Jeremy Chia, Soap Cycling Singapore ## 予算は増加傾向、インフラコストはそれ以上に アナリティクスエンジニアリングへの投資は続いていますが、成長は不均一です。 2026年、**36%の回答者がチーム予算の増加を報告**し、28%が変化なし、14%が減少、19%が自チームの予算状況を把握していません。 ![Image](https://cdn.sanity.io/images/wl0ndo6t/main/b574bdb73ef11a1fc33e8a515714de48164bbe49-1112x584.png) 同時に、データウェアハウス・コンピューティングリソース・データ管理ソフトウェアなど、アナリティクスとAIインフラへの支出はより広く増加しています。 ウェアハウスとコンピューティングの費用は57%が増加を報告し、減少を報告したのはわずか13%。 ![Image](https://cdn.sanity.io/images/wl0ndo6t/main/1635a3737dac0fbd1424a46a7657fefa21cdcec2-1112x584.png) 予算の増加とインフラの増加は連動していません。ウェアハウスとコンピューティングの費用増加を報告するチームの方が、予算拡大を報告するチームより多くなっています。 ![Image](https://cdn.sanity.io/images/wl0ndo6t/main/d0caf105dc43dd28518d18ca9ab11eced65fc3d8-1112x546.png) 直近1年間の回答分布を見れば、その差は一目瞭然です。 ![Image](https://cdn.sanity.io/images/wl0ndo6t/main/b18bff801c7930b16a3766421f3aca24e260ce36-1112x764.png) 予算とインフラ支出の両方が増加しているチームが多い一方、ウェアハウスとコンピューティングの支出はより高い成長帯に集中しており、拡大のペースが不均一であることを示しています。 インフラコストが全体予算を上回るペースで増加すると、チームは持続的な財務的プレッシャーの下で動くことになります。 ワークロードとデータ消費が拡大するにつれ、コンピューティングの需要もそれに伴って増加します。コスト最適化は縮小のサインではなく、スケールを維持するための必然的な対応です。 *** ### 今後の投資優先事項 リーダー層は今後12ヶ月でデータツールへの投資を増やすことを優先する傾向にあります。予算の拡大とともに、長期的なチーム能力の強化を重視していることが表れています。 ![Image](https://cdn.sanity.io/images/wl0ndo6t/main/b63db40ed4083afdd049f6e87a7dfc7b3e9d7e3b-1112x584.png) この違いは役割の責任を反映しています。リーダーは通常、長期的な投資計画とプラットフォーム能力に注目し、実務担当者は日々の実行と運用上の制約により密接に結びついています。 #### このことが意味するもの 3分の1以上のチームが予算増加を報告している一方で、より多くのチームがウェアハウスとコンピューティングの支出増加を報告しています。AI主導のワークロードが拡大するにつれ、インフラの需要がその投資の多くを吸収しています。これはアナリティクスチームへの財務的プレッシャーを高め、投資の意思決定をより重要なものにしています。 管理を維持するため、チームはインクリメンタル処理・クエリ最適化・コスト可視化を優先しています。効率化はもはや任意ではなく、スケールでの成長を持続させるために不可欠です。 コスト最適化は、増加するワークロード強度の下でスケールを維持しようとするチームにとって優先事項であり続けます。2026年の財務規律とは、単なる削減ではなく、成長が持続可能であることを確かにすることです。 ## アーキテクチャへの関心はある、採用はまだこれから モダンデータ基盤への関心は高まっていますが、本番での本格採用はまだ限定的です。 オープンテーブルフォーマットやマルチエンジン対応への関心が、複雑なデータ環境を持つ組織の間で戦略的な話題として浮上しています。今年の調査に含まれたApache Icebergは、その動きを示す早期シグナルのひとつです。 2026年、本番環境でIcebergを使用しているのはわずか9%で、6%が採用を計画中、12%がPoCの段階にあります。合計で27%が何らかの関与を報告している一方、68%は現在計画がないと回答しています。 ![Image](https://cdn.sanity.io/images/wl0ndo6t/main/8d4d0a9add2f0442d869be005bcdb04a8002b0c0-1112x584.png) Icebergを評価または採用しているチームの中では、いくつかの動機が関心を促しています。最も多く挙げられたのはマルチエンジン互換性（22%）で、次いで柔軟性とパフォーマンスへの考慮が続いています。 ![Image](https://cdn.sanity.io/images/wl0ndo6t/main/d7a6f5665c3ba865278b1e37d9ecf381b0a8e723-1112x778.png) 一方、Icebergを評価中の組織からは、採用を慎重にさせる懸念も聞かれます。最も多く挙げられたのは、知識・ノウハウの不足（27%）とユースケースが明確でない（27%）の2点です。コンセプト自体への抵抗ではなく、実装の複雑さに向き合っている段階と言えます。 マルチエンジン対応や相互運用性は、戦略的な優先事項として注目度が高まっています。ただし、ほとんどのチームはまだ評価・初期採用の段階にあります。アーキテクチャの議論は2026年の戦略テーブルに上がり始めていますが、日常の運用を変えるにはまだ至っていません。 ![Image](https://cdn.sanity.io/images/wl0ndo6t/main/aaffd0ee549505650b53f4213598d13780e069f1-1112x778.png) #### このことが意味するもの Icebergを検討しているチームは全体の4分の1を超える一方で、実際に本番環境へ導入しているのは10チームに1チームもありません。オープンテーブルフォーマットやマルチエンジン間の相互運用性への関心は高まっているものの、ほとんどの組織は依然として評価や実験の段階に留まっており、アーキテクチャの全面的な移行には至っていないのが現状です。 調査データからは、Icebergが「差し迫った運用の切り替え」ではなく、「戦略的で先見性のある投資」と見なされていることが伺えます。高い関心は長期的な計画や将来を見据えた姿勢の表れである一方、本番導入が限定的なのは、大規模なコミットの前に、技術の成熟度やツール群の整備状況、そして社内の対応能力を慎重に見極めているためでしょう。 2026年においてアーキテクチャは重要なテーマではあるものの、日常の運用を左右する主要因にはまだなっていません。 *** ## 次のステージへ ー 加速の時代における信頼のスケール化 2026年の調査が示す現実は明確です。**AIはガバナンスの成熟が追いつくよりも速く、アウトプットを拡大しています。** 2026年の現場では、加速と制約が同時に起きています： - AIを活用したコーディングが開発ワークフローに定着 - AI生成インサイトが増大するスピードと規模でステークホルダーに届いている - インフラの需要が高まっている - 信頼への期待が強まっている - データ品質・オーナーシップのあいまいさ・ガバナンスのギャップが続いている **その結果、アナリティクスエンジニアリングには新たな責任が生まれています。それは、AI生成インサイトが、既存の信頼のギャップをさらに広げないよう守ること。**そしてこの環境で差をつけるのは、アウトプットの量ではなく信頼性です。スケールしながら、監視のもとで、明確なガバナンスとともに。 AIの次のフェーズは「生成」から「実行」へと移ります。システムが自律的にワークフローを動かし、アウトプットを検証し、人手をかけずにツール間を横断するようになります。品質管理・レビュー・ガバナンスがこの変化に追いつかなければ、自律性は問題を解決するのではなく、複雑さを増やすだけになります。**規律こそが、自律性の前提条件です。** **アナリティクスエンジニアリングはますます、責任によって定義される分野になっています ー **アウトプットとともに、信頼もスケールさせる能力です。新しいことができるようになるほど、その広がりを決めるのは信頼です。次のフェーズで成功する組織は、信頼をインフラとして扱い、ガバナンス・データ品質・日々の運用に組み込んでいます。 **2026年、強いチームの共通点は規律。** > > > — Pip Sidaway, nib *** ## 調査方法 dbt Labsは2025年12月5日から2026年2月1日にかけて、様々な業界・地域のデータ実務者とリーダー363名から回答を収集しました。回答者の73%が実務担当者、27%が管理職または幹部職です。 結果は[2025年版レポート](https://www.getdbt.com/resources/state-of-analytics-engineering-2025)と比較し、前年からの変化を把握しています。 パーセンテージは各選択肢を選んだ回答者の割合を示しています。複数選択の質問では合計が100%を超える場合があります。一部のチャートでは非回答を除外していますが、割合は常に総回答者数をベースに計算しています。数値は読みやすさのために整数に丸めているため、合計が1ポイント前後する場合があります。 2026年の回答者層は業界・報酬・役割において2025年と概ね同様です。中堅～シニアレベルの経験豊富なプロフェッショナルが多く、実務・戦略の両面での意思決定者の声を反映しています。 ### 調査回答者プロフィール アナリティクスエンジニアリングは業界・地域を問わず広がり続けています。 回答者はテクノロジー・金融・ヘルスケア・小売など多様な業界にわたっており、コンプライアンスやデータの信頼性が重要な分野での参加も目立ちます。テクノロジー業界が引き続き最多を占めており、規制の厳しい業界での参加増加は、エンタープライズ環境でのアナリティクスエンジニアリングの重要性の高まりを示しています。 ![Image](https://cdn.sanity.io/images/wl0ndo6t/main/1f5eacf50caa61224afbf8c7a9dcbe3606e01e55-1112x690.png) 参加者は北米とヨーロッパに集中しており、成熟したデータエコシステムの存在を反映しています。 ![Image](https://cdn.sanity.io/images/wl0ndo6t/main/03cc95a9b58b7037481cda62dbfab1cd96cefca3-1112x560.png) アナリティクスエンジニア・データエンジニア・アナリスト・データサイエンティストが引き続き中心的な職種を構成しています。 ![Image](https://cdn.sanity.io/images/wl0ndo6t/main/24d4efe7b38d8bee2ad099251b72e7291c5f4a2f-1112x586.png) この分野は実務担当者主導です。73%が実務担当者、27%が管理職・幹部職として勤務しています。 ![Image](https://cdn.sanity.io/images/wl0ndo6t/main/cd185389bd5166516f4c6e4779ca4fd297ef3517-1112x584.png) 報酬面では、北米の実務担当者の80%以上が年収10万ドル以上を報告しており、アナリティクス人材への継続的な需要がうかがえます。マネージャーレベルの報酬は特に北米で高い帯に集中しており、ヨーロッパでは地域差が残っています。 ![Image](https://cdn.sanity.io/images/wl0ndo6t/main/1c549d550676cee9364ce6b9391d45fe8f079a25-1112x544.png) ![Image](https://cdn.sanity.io/images/wl0ndo6t/main/8f2a19b8816072386a66f7b422363b3e3085a73e-1112x584.png) AIの活用が進み期待値が高まる中でも、アナリティクスエンジニアリングの日々の仕事はデータのメンテナンスと整理が中心です。 多くの回答者が、業務時間の大半をデータセットの維持・整理に充てていると回答しています。加速がワークフローを変えつつも、こうした基盤的なデータ作業は依然として欠かせません。 ![Image](https://cdn.sanity.io/images/wl0ndo6t/main/6d5f3863c489cb5907d55d13da7c7bba1aa79e1c-1112x584.png) #### このことが意味するもの 2026年のアナリティクスエンジニアリングは、実務担当者が中心となり、エンタープライズに深く組み込まれ、スケールで動いています。AIの活用が加速し期待が高まる中、このコミュニティはイノベーションと運用上の責任を両立させながら、その戦略的な役割を広げています。 #### そして最後に… LLMやガバナンスフレームワークが語られる時代になっても、永遠に続く議論はあります。 ![Image](https://cdn.sanity.io/images/wl0ndo6t/main/4b5ab26bcfcc9fa329a47646883e00459240ae9e-1112x524.png) データが示すのは、データガバナンスの合意はランチの注文より簡単かもしれない、ということです。 意見が真っ二つに割れる質問もありました。: 飛行機の座席を倒す行為は許容されるべきだと思いますか？ ![Image](https://cdn.sanity.io/images/wl0ndo6t/main/7a0ce937e3af133a866fd9eb143f83809411a68a-1114x526.png) 意見は真っ向から分かれており、共通認識は見られません。ガバナンスのあり方は、たとえ抽象的な議論の段階であっても、蓋を開けてみれば千差万別であることが分かります。 すべてのダッシュボードとパイプラインの背後には、ともに複雑さに向き合うコミュニティがあります。2026年が証明するのは——アナリティクスエンジニアリングの未来を定義するのはツールではなく、いつ信頼し、いつ検証すべきかを知っている人々だということです。 #### **2026年 アナリティクスエンジニアリング最新動向ウェビナーのご案内** AIがスピードを加速させる一方で、データの信頼性とガバナンスへのプレッシャーも高まっています。あなたのチームは、このバランスをどうとりますか？ データ・アナリティクスの第一線で活躍する3名のエキスパートが、レポートの知見をもとに現場のリアルを語ります。 [レポートの深掘りウェビナーに参加する →](https://www.getdbt.com/jp/resources/webinars/2026-state-of-analytics-engineering-virtual-event-japan) --- --- title: "Stay up-to-date" description: "Join the dbt Labs newsletter to receive the latest insights, product updates, and best practices in analytics engineering directly to your inbox." url: "https://www.getdbt.com/learn/newsletter" --- ## Stay up-to-date Subscribe to newsletters, blog posts, and podcasts from dbt Labs. *** ## Other ways to stay connected ### Analytics Engineering Roundup newsletter Get a weekly digest of articles on analytics engineering and its adjacent ecosystem, by Tristan Handy and Anna Filippova. [Subscribe now](https://roundup.getdbt.com/) ### Analytics Engineering podcast Subscribe to a biweekly podcast, co-hosted by Tristan Handy and Julia Schottenstein, featuring conversations with data practitioners building the future of analytics engineering. [Listen on Apple Podcasts](https://podcasts.apple.com/us/podcast/the-analytics-engineering-podcast/id1574755368) ### Join the Community The dbt Community connects you with thousands of data practitioners, leaders, and learners—all solving real problems, sharing best practices, and growing their careers together. [Join the Community](https://www.getdbt.com/community/join-the-community) --- --- title: "Legal - AI principles at dbt Labs" description: "Explore dbt Labs' AI principles, focusing on ethical, transparent, and responsible AI use to build trust in data practices." url: "https://www.getdbt.com/legal/ai-principles" --- # The dbt Labs AI Development Principles *** ### **The dbt Labs AI Development Principles** We believe that Generative AI, Large Language Models, Machine Learning technologies, and other automation and computer reasoning tools—for simplicity, let’s just call these AI Technologies—are capable of significantly enhancing the experience of dbt Cloud users. Our product and engineering teams are working with a number of these AI Technologies today, looking for ways to make data transformation more accessible and efficient. We know that we can only succeed in our mission if our users trust us to build and release features that use these AI Technologies safely and we see transparency as our North Star, so in that vein we want to share with you our intentions and principles for leveraging AI Technologies in our platform including your ability to control the use of these technologies for your account. For clarity, our platform means dbt Cloud and not customer support, documentation search, or internal tooling that we may use ourselves. ### A Note About “Data” Our [Terms of Use](https://www.getdbt.com/terms-of-use) define two categories of “data” and understanding them is important for knowing how we intend to leverage AI Technologies. The first category is “Client Data” which includes materials, information, or content that users share or input into dbt Cloud. This category can include your queries, column names, table names, lineage, data previews, and any table data. We treat this data as confidential and we protect it as if it were our own sensitive data. We will only use Client Data to provide services to the specific client that uploaded that data. The second category is “Platform Data” which includes data generated by dbt Cloud in the service of processing user requests. These may be SQL commands that don’t include any specific data from a customer table or performance metrics, system logs, or anonymized usage statistics. This data is not confidential between us and may be used for purposes of improving our platform and the user experience for all dbt Cloud users. When using dbt Cloud to run transformations, the data from your data warehouse remains in your data warehouse. We utilize AES-256 for all data encrypted at rest and TLS 1.2+ for data in transit. For more information about our general security practices and our practices specific to data processing, please see our [Security page](https://www.getdbt.com/security). ### AI Partners and Engines The first features we are releasing that leverage AI Technologies are powered by third-party large language model providers. Where we contract with a third-party provider for these services, we do not allow them to use any of our client data or platform data to train their models. In addition, we require that any data sent to a third-party provider, including prompts that we write and data that you supply, may only be retained for a short period of time in their systems. ### **Model training** We may use your Client Data to train our AI models to improve your experience with the platform and not for the benefit of other users. We will not allow your Client Data to be used to train third-party provider models. We do not currently use Client Data for any internal model training, but if we introduce those features in the future, we will provide a disclosure to you through the dbt Cloud application or direct communications before enabling the features and allow you to opt-out of using our AI features. We may use Platform Data to train internal AI models to improve the platform generally. This data will be de-identified and aggregated before being used for model training. We see this data as providing opportunities to improve our overall platform performance. We do not currently use Platform Data for any internal model training, but should we introduce those features in the future, we will inform you. You will not have an ability to opt-out of this type of training. ### **AI Account Settings** Account administrators can control the use of AI Technologies in our platform for account users and model training via toggles on the account settings screen. If an account chooses to opt-out of AI features, the UI elements for those features will still be visible but interaction with elements will result in a message to the user that the feature is not available in their account and they should engage with an account administrator to enable it. Administrators can change the AI account settings at anytime. These settings control: - **Access to AI features** - AI features are set to “opt-in” by default for all accounts in all plans unless we have a prior agreement with you to disable these features in your account. - Enabling the AI features is an all-or-nothing option. That is, you cannot choose to opt-out of certain AI features and opt-in to others. - **Model training** - We will never allow third-party providers to train their models using either your Client Data or our Platform Data. For internal models, because we do not currently do any training of internal models, there are no options yet. If we do release a feature that uses Client Data to train models, there will be an option to opt-out of training available to account administrators. ![AI Cloud settings in dbt Cloud](https://cdn.sanity.io/images/wl0ndo6t/main/7cc7ef5a8143a9d393ff11b8cacacb94378e2a98-1832x874.jpg) Enterprise customer agreements that are governed by MSAs are more complex and may include specific requirements related to these features. Some customers may have stringent regulatory or compliance requirements related to their data and would prefer to opt-out. If your agreements with us specify that your account should be opted-out of AI features, we will administratively opt the account out. An account administrator can opt-in at any time. ### Future Features We may release new AI features that are sold as an add-on to the base dbt Cloud platform. If we do this, the principles above will still apply and your Client Data will be treated confidentially and only used to train models for your specific use. We will be clear and transparent about the behavior of these features as they are released. --- --- title: "Legal - Certification Terms" description: "Review the terms for dbt certification, including eligibility, exam rules, confidentiality, and use of credentials." url: "https://www.getdbt.com/legal/certification-terms" --- # dbt Certification Program Terms and Conditions *** _Last updated: May 25, 2022_ These dbt Certification Program Terms and Conditions (this “**Agreement**”) are entered into between you (“**you**”) and dbt Labs, Inc. (“**dbt Labs**,” “**we**,” “**us**,” or “**our**”) as of the date you click “Agree and Continue” below (the “**Effective Date**”). This Agreement contains the terms and conditions that govern your participation in the dbt Certification Program and may be updated from time to time. YOU MAY TAKE THE DBT CERTIFICATION EXAM(S) ONLY IF YOU AGREE TO THE TERMS AND CONDITIONS OF THIS AGREEMENT. IF YOU DO NOT AGREE, THEN DO NOT CLICK “AGREE AND CONTINUE.” ## Participation in the dbt Certification Program To participate in the Certification Program, you must: 1. Agree to the terms and conditions of this Agreement; 2. Be at least 18 years of age and register under your full legal name (a valid government-issued photo ID is required); and 3. Take the exam(s). To obtain a dbt certification, you must receive a passing score. Each dbt certification is valid for two (2) years from the date of passing the applicable exam. All fees paid in connection with the Certification Program are in U.S. dollars. ## Confidential Information The exams are the confidential property of dbt Labs (“**Confidential Information**”) and are made available to you for the sole purpose of testing your knowledge in the area referenced in the applicable exam. You agree (i) to hold Confidential Information in confidence and take all reasonable precautions to protect it; (ii) not to use Confidential Information, except as provided herein; and (iii) not to disclose, publish, reproduce or transmit any Confidential Information to any third party, in any form. dbt Labs retains all rights, title and interest in and to all information, content and data contained in exams and all copyrights, patent rights, trademark rights and other proprietary rights thereto provided by dbt Labs under this Agreement. ## Personal information If you choose to participate in the Certification Program, as part of the exam process, you must provide personal information, which may be collected during registration, via the exam, and/or when interacting with web pages related to the exam. This information will be used to facilitate and process the exam and determine whether a credential may be issued to you. Your participation and any dispute over privacy is subject to the dbt Labs Privacy Policy, the current version of which is available at [https://www.getdbt.com/cloud/privacy-policy/](https://www.getdbt.com/cloud/privacy-policy). Unless stated otherwise, the dbt Labs Privacy Policy applies to all information that we have about you and your account. You agree that we may share your information with our third-party contractors in connection with the administration of certification exams. dbt Labs is not responsible for any third-party contractors and you may be required to enter into separate terms and conditions with the third-party providers. We may also verify the status of your dbt certifications to any third parties who inquire about such status. ## Use of name and logo Subject to the terms of this Agreement and dbt Labs’s Trademark Policy located at [https://www.getdbt.com/trademark-guidelines](https://www.getdbt.com/trademark-guidelines) (subject to change at our discretion), we grant you the non-exclusive, non-transferable, limited personal right to use the name of the specific dbt certification that you have received, the dbt Labs name, logo and the digital badge of the specific certification that you obtained, on your personal resume, website, business cards, letterhead and social media solely in relation to your current, valid dbt certification. We may revoke your right to use any dbt Labs marks at any time by giving you written notice. Furthermore, you will not misrepresent or embellish the relationship between us and you (including by expressing or implying that we support, sponsor, endorse, or contribute to you or your business endeavors), or express or imply any relationship or affiliation between us and you or any other person or entity except as expressly permitted by this Agreement. ## Term The term of this Agreement begins on the Effective Date and continues until the later of (i) termination of your access to the Certification Program; or (ii) until you no longer hold a valid dbt certification. ## Indemnification You will defend, indemnify, and hold harmless us, our affiliates and licensors, and each of their respective employees, officers, directors, and representatives from and against any claims, damages, losses, liabilities, costs, and expenses (including reasonable attorneys’ fees) arising out of or relating to any third party claim concerning: (a) your participation in the Certification Program; (b) your use of any dbt Labs logo in a manner not authorized by or consistent with this Agreement; (c) any representations, warranties, or guarantees you make to third parties with respect to dbt Labs; (d) any misrepresentation or embellishment by you of your relationship with dbt Labs; or (e) your breach of this Agreement. dbt Labs may assume control of the defense and settlement of the claim at any time. ## Disclaimers DBT LABS MAKES AND YOU RECEIVE NO WARRANTIES OR CONDITIONS OF ANY KIND, EXPRESS, IMPLIED OR STATUTORY, RELATED TO OR ARISING IN ANY WAY OUT OF THIS AGREEMENT. DBT LABS SPECIFICALLY DISCLAIMS ANY IMPLIED WARRANTY FOR MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT OF ANY THIRD PARTY RIGHTS. ## Limitations of Liability The certification exam(s) may be administered by an independent testing vendor. dbt Labs has no liability to you for any claim in any way related to the certification exams, including but not limited to registration, delivery of the certification exams, and the accuracy, timeliness or reporting of certification exam results. DBT LABS SHALL NOT BE LIABLE FOR ANY INDIRECT, INCIDENTAL, SPECIAL,PUNITIVE, OR CONSEQUENTIAL DAMAGES OR ANY LOSS OF PROFITS, REVENUE, DATA OR USE. DBT LABS’S LIABILITY FOR DIRECT DAMAGES, WHETHER IN CONTRACT, TORT OR OTHERWISE, SHALL BE LIMITED TO THE FEES PAID TO DBT LABS UNDER THIS AGREEMENT. ## Trade compliance You represent and warrant that you are not subject to sanctions or otherwise designated on any list of prohibited or restricted parties, including but not limited to the lists maintained by the United Nations Security Council, the U.S. Government (e.g., the Specially Designated Nationals List and Foreign Sanctions Evaders List of the U.S. Department of Treasury, and the Entity List of the U.S. Department of Commerce), the European Union or its Member States, or other applicable government authority. ## Code of Conduct You will comply with all rules and regulations applicable to the administration of the certification exam(s) as set forth by dbt Labs or by a certification exam provider. You will not engage in any misconduct in connection with the certification exam, including without limitation: (a) receiving or providing unauthorized assistance, or submitting work that is not your own; (b) possession or use of unauthorized materials during any certification exam; (c) falsifying your identity or identification documents, or misusing any testing identification number, username, or other credentials that have been provided to you; (d) failing to adhere to any testing policy, procedure, or directions; (e) disclosing or disseminating the content of any certification exam; (f) use of any dbt Labs trademarks in a manner not authorized by this Agreement and the dbt Labs’s Trademark Policy; or (g) any other actions that we believe are inconsistent with the principles of the Certification Program. ## Action for non-compliance If for any reason and at its sole discretion, dbt Labs believes your exam result does not accurately reflect your true knowledge or mastery of the subject matter of the test and/or that you have violated the compliance terms set forth herein, dbt Labs may (without refund of any kind) deny you any further participation in the certification exam, cancel a passed exam result, revoke any pre-existing dbt Labs certifications, your dbt certification status and any other rights previously conferred on you by dbt Labs, and bar you from any further participation in dbt Labs certification program. ## General dbt Labs reserves the right to modify the Certification Program, credential requirements, digital badges and exams from time to time without notice, This Agreement, and any claim, controversy or dispute arising from or related to this Agreement, is governed by and construed in accordance with the laws of the State of Delaware without giving effect to any conflicts of laws provisions. Any claim, suit, action or proceeding arising out of or relating to this Agreement or its subject matter will be brought exclusively in the state or federal courts of Wilmington, Delaware, and each party irrevocably submits to the exclusive jurisdiction and venue of such courts in connection with the Agreement. A waiver by a party under this Agreement is only valid if in writing and signed by an authorized representative of the waiving party. A delay or failure of a party to exercise any rights under this Agreement will not constitute or be deemed a waiver or forfeiture of such rights. This Agreement represents the complete agreement between the parties with respect to its subject matter and supersedes all prior and contemporaneous agreements and proposals, whether written or oral, with respect to such subject matter. If any provision of this Agreement is held by a court of competent jurisdiction to be invalid or unenforceable, the remaining provisions of this Agreement will remain in effect to the greatest extent permitted by law. Neither party is responsible for non-performance or delay in performance of its obligations under this Agreement due to force majeure events beyond its reasonable control, including acts of government, floods, fires, earthquakes, civil unrest, acts of terror, epidemics, quarantine restrictions, strikes or other labor disruptions, internet or service provider failures, or denial of service attacks. Provisions that survive termination or expiration of this Agreement include those pertaining to limitation of liability, disclaimer of warranty, indemnification, confidentiality, and others which by their nature are intended to survive. --- --- title: "dbt Wizard token costs" url: "https://www.getdbt.com/legal/dbt-wizard-token-costs-by-model" --- ## Model Provider Rate Table _Effective September 14, 2026_ This model rate card applies to the [dbt Labs Service Consumption Table](https://www.getdbt.com/legal/service-consumption-table). --- --- title: "dbt Labs Service Consumption Table" url: "https://www.getdbt.com/legal/service-consumption-table" --- ## **dbt Labs Service Consumption Table** _Effective July 1, 2026_ This dbt Service Consumption Table (the “**Table**”) applies whenever a customer (“**Customer**”) of dbt Labs, LLC (as successor in interest to dbt Labs, Inc.) (“**dbt Labs**”) uses a Consumption Commit Add-on Product (as defined below) and as described more fully in your agreement, Order Form and/or similar agreements with dbt Labs (“**Agreement**”). **1. Definitions** Any capitalized terms not defined herein will have the meanings given to them in the Agreement or, if not defined in the Agreement, in the Terms of Service located at [https://www.getdbt.com/terms-of-service](https://www.getdbt.com/terms-of-service) (or such successor URL as may be designated by dbt Labs). “**Arrears**” means the period of continued use of Consumption Commit Add-on Products on an Upfront Commit Plan after the Consumption Pool has been depleted. “**Billing Period**” means a calendar month running from the first to the last day of the month. “**BYOK**” (Bring Your Own Key) means Customer’s use of a Consumption Commit Add-on Product with Customer’s own AI model provider credentials. “**Committed Use Discount**” means the discount that may be provided to Customer in its applicable Order Form, in exchange for Customer’s commitment to spend certain amounts on an Upfront Commit Plan. “**Consumption Commit Add-on Product**” means those dbt Labs products identified in this Table, as updated from time to time, that Customer accesses and uses on a consumption basis, whether by purchase or under a trial. “**Consumption Pool**” means the total dollar amount of the prepaid, fungible consumption pool that Customer purchases via its Order Form that draws down as Customer uses the Consumption Commit Add-on Products on an Upfront Commit Plan. “**Monthly Spend**” means the aggregate dollar amount consumed each Billing Period from the Consumption Pool based on actual use of any Consumption Commit Add-on Product(s). “**Monthly Plan**” means a plan where Customer is billed for the costs incurred during the prior Billing Period. “**Upfront Commit Plan**” means a subscription‑based plan which requires an upfront one-time purchase of a Consumption Pool. **2. Consumption** 2.1 _Upfront Commit Plans_**.** Customer’s use of the Consumption Commit Add-on Product(s) on an Upfront Commit Plan will be drawn down from Customer’s Consumption Pool as specified in the applicable attached Appendix for the relevant Consumption Commit Add-on Product. If Customer has multiple Accounts on a single Upfront Commit Plan, Customer’s Consumption Pool may be applied toward any of the Accounts. When Customer’s Consumption Pool is depleted but Customer continues to use the Consumption Commit Add-on Products, dbt Labs will notify Customer it is entering Arrears and Customer will have the option to purchase additional Consumption Pools. If Customer is in Arrears, Customer will be billed monthly based on its Monthly Spend. Customer may continue using the Consumption Commit Add-on Products in Arrears so long as Customer is in compliance with this Table and the Agreement, including all payment obligations thereto. 2.2 _Monthly Plans**. **_Customer will be billed for its Monthly Spend incurred on any Consumption Commit Add-on Product(s) used during the prior Billing Period. **3. Changes, Updates and Future Consumption Commit Add-on Products. **dbt Labs may update this Table from time to time. If we do make updates, we will update the Effective Date at the top of this Table. Unless the Agreement supersedes this Table, any updates will become effective for Customer upon renewal or entry into a new Order Form after the updated version of this Table goes into effect. If we make a material update, we will use reasonable efforts to alert Customer through the dbt platform dashboard or via email prior to the update taking effect. For clarity, any updates that are required by applicable law or related to a new feature or product release will be effective upon notice to Customer and, following such notice, Customer’s continued use of the future feature or product on or after the Effective Date thereof, constitutes Customer’s acceptance of the updated version. **4. Conflict. **In the event of any conflict between this Table and the Agreement, this Table will prevail with respect to the subject matter described herein. **Appendix A: dbt State Consumption Rate Table** _Effective July 1, 2026_ This dbt State Consumption Rate Table (“**Appendix A**”) governs Customer’s consumption of dbt State. _Definitions:_ "**Daily Active Target Table**" or "**DATT**" means the number of distinct Target Tables for which dbt State performs at least one of the following unique operations on a given day (based on UTC time): a skip, clone, or test reuse. All reuses of the same active Target Table in a single day (based on UTC time) are counted as a single DATT. "**Target Table**" means a database object managed by Customer’s dbt project for a given database and schema name, including seeds, snapshots, dbt models (including incremental models), and each distinct test (even if the tests are not built into the database because store_failures is disabled), where dbt State is able to reuse the Target Table based on Customer’s configuration rules. (For example, if stg_customers has not_null and unique tests on its id column, there are three Target Tables: the model and its two tests). _Description:_ dbt State is billed at a list rate of $0.094 per DATT (the "**DATT Rate**"), unless a Committed Use Discount or other discount is reflected on Customer's Order Form. Monthly Spend is calculated by summing the total number of DATT attributable to Customer's use of dbt State across Customer's Account(s), and multiplying it by the DATT Rate. For Customers on an Upfront Commit Plan, Monthly Spend will be applied against Customer's Consumption Pool. During any period in which Customer is in Arrears, Customer's continued use of dbt State remains subject to the DATT Rate, unless a Committed Use Discount is reflected on Customer’s Order Form. If a discount is reflected, the Committed Use Discount will apply to the DATT Rate for the first two (2) Billing Periods in Arrears. Beginning with the third (3rd) Billing Period in Arrears, any Committed Use Discount will no longer apply, and use of dbt State will be billed at the full DATT Rate. **Appendix B: dbt Wizard Consumption Rate Table** _Effective August 25, 2026_ This dbt Wizard Consumption Rate Table (“**Appendix B**”) governs Customer’s consumption of dbt Wizard. _Definitions:_ “**Consumption Unit**” means the common unit of 1 (one) million Tokens into which usage of each Consumption Commit Add-on Product is converted and then billed to Customer. “**Managed AI**” means the AI models that dbt Labs makes available and manages on Customer’s behalf for Customer’s use of a Consumption Commit Add-on Product (as opposed to BYOK). “**Model Provider**” means a third‑party provider of AI models made available through Managed AI, including cloud‑hosted equivalents. “**Token**” means the unit of AI model usage (e.g., input and output tokens) used to meter Managed AI usage of dbt Wizard. _Description:_ dbt Wizard allows Customers to access multiple third-party AI models provided by Model Providers. dbt Labs does not own or operate the third-party AI models accessed via dbt Wizard, and does not control the availability, pricing, performance, or outputs of such models. Context-window limits may apply to the supported third-party AI models. Where Customer uses dbt Wizard with Managed AI, usage is measured per the model and Token type and billed at the Model Provider’s rates set out in the Model Provider rates dashboard at [https://www.getdbt.com/legal/dbt-wizard-token-costs-by-model](https://www.getdbt.com/legal/dbt-wizard-token-costs-by-model) (“**Model Provider Rate Table**”). Committed Use Discounts do not apply to the Model Provider Rate Table. If Customer uses dbt Wizard via BYOK, the Model Provider Rate Table does not apply and Customer’s AI model usage via dbt Wizard will be billed by Customer’s chosen Model Provider directly. If Customer uses dbt Wizard under an Upfront Commit Plan, Customer’s usage is metered pursuant to the Model Provider Rate Table then converted into a Consumption Unit which draws down from the Customer’s Consumption Pool. For Customers under a Monthly Plan, dbt Labs may make dbt Wizard available for trial use, subject to a one‑time trial credit pool (the “**Trial Credits**”). The Trial Credits are available solely for Customer’s trial use of dbt Wizard. Once Trial Credits is depleted, Customer’s continued use of dbt Wizard requires purchase of dbt Wizard as a Consumption Add-On Product pursuant to the Table. For Customers under an Upfront Commit Plan, dbt Labs may make available a free, recurring pool of consumption credits, allotments, or promotions (“**Free Credits**”) that the Customer may use toward dbt Wizard. Once Free Credits have been depleted during the relevant Billing Period, Customer’s continued use of dbt Wizard will draw down from Customer’s Consumption Pool. Notwithstanding anything to the contrary within the Table, dbt may update this Appendix and the Model Provider Rate Table from time to time, including to add, remove, or change third-party models, update or reflect changes to the Model Provider’s rates, or to change Managed AI pricing for dbt Wizard. With the exception of updates to the Model Provider Rate Table that reflect Model Providers’ rate changes, if dbt Labs makes an update to dbt Wizard’s Managed AI pricing, dbt Labs will provide Customer 30 days’ written notice prior to the update taking effect, and Customer’s continued use of dbt Wizard via Managed AI on or after the effective date thereof constitutes Customer’s acceptance of the updated pricing. --- --- title: "dbt Licensing - Public FAQs" description: "Explore dbt Labs’ licensing for dbt Core and Fusion. Learn about the Apache 2.0 licenses, the dbt Product Licensing Agreement, and usage guidelines." url: "https://www.getdbt.com/licenses-faq" --- ## dbt Licensing FAQ The goal of this document is to give maximal clarity under the permitted use of various codebases and products maintained by dbt Labs. If you have any questions please reach out to license@dbtlabs.com. ### Change history #### May 28, 2025 - Posted original FAQ. #### June 1, 2026 - Removed ELv2 references, because the dbt-fusion repository has moved to the dbt-core repository and been relicensed as Apache 2.0 - Introduced the [dbt Product Licensing Agreement](https://www.getdbt.com/dbt-fusion-engine-license-agreement) that governs the dbt Fusion binary’s usage - Added FAQs related to the Apache 2.0 release of dbt Core v2.0 - Removed references to the Business Source License, because MetricFlow was relicensed as Apache 2.0 in October 2025. *** ## Announcing dbt Core v2.0 and Fusion: two distributions powered by a single engine On May 28, 2025, dbt Labs announced the next-generation dbt Fusion engine, which is faster, more capable, and more efficient than the Python engine that powers dbt Core v1.x. On June 1, 2026, dbt Labs announced that the dbt Fusion engine will power both the dbt Core (OSS) and Fusion (proprietary) distributions of the dbt v2.0 framework, and that the corresponding code has been published to the dbt-core repository under the Apache 2.0 license. ### Is the license for dbt Core v1.x changing? No, it is still Apache 2.0. ### Is the license for dbt Core v2.x changing compared to v1.x? No, it is Apache 2.0 as well. ### Will dbt Labs continue to support and maintain dbt Core? Yes. ### What is the difference between the dbt Core and Fusion distributions? Version 2 of the dbt framework has two distributions which can both be installed locally for free, powered by a single engine: - dbt Core is completely open-source. Its code and binary are subject to the Apache 2.0 license. - dbt Fusion extends dbt Core with additional proprietary code to create an enhanced binary with additional features. Teams (and even other competitive vendors) can use the Fusion distribution for free, subject to a handful of basic provisions described below. Some additional features of the dbt Fusion distribution require a dbt platform account or paid subscription. We recommend that most teams install the dbt Fusion distribution, which has more capabilities available than its Apache counterpart even if you never engage with dbt Labs. ### What happened to the ELv2-licensed code in the dbt-fusion repository? It is now in the dbt-core repository under the more permissive Apache 2.0 license. The additional code necessary to build a Rust implementation of dbt Core – which we previously committed to releasing under the Elastic License (ELv2) by the time the dbt Fusion engine reached General Availability – has also been moved into the dbt-core repository as Apache 2.0 code. ### Do I need a dbt platform account, or to be a paying dbt platform customer in order to use dbt Fusion? No. ### Do I need a dbt platform account, or to be a paying dbt platform customer in order to access some premium features of dbt Fusion? Yes. ### Is there any limit to the number of users at a company who can use the dbt Fusion CLI for free? No. ### What do I, a dbt Core user, need to know about dbt Fusion? As long as you aren't offering dbt Fusion as a hosted or managed service to a third party, you should think about using dbt Fusion in almost exactly the same way you think about using dbt Core today. It’s free, you can contribute to its development, and you can adopt it across your organization without asking permission or changing your existing deployment method. You can use dbt Fusion internally in your own business, for free and without restriction. This includes using dbt Fusion to provide transformed data to other customers. However, if you are providing your customers a product with dbt Fusion embedded, you must permit your customers to use the full features of dbt Fusion, including login-gated features if they choose. *** ## Licenses ### What licenses does dbt Labs use for dbt products? dbt Labs uses different license types for different software offerings: - dbt Core is released under the [Apache 2.0 license](http://www.apache.org/licenses/LICENSE-2.0), which is an Open Source software license that permits anyone to use, copy, redistribute, or modify the licensed software without warranty, conditions, or limitations, aside from the requirement to preserve license notices, attribution, and trademarks. - dbt Fusion is proprietary to dbt Labs and extends the capabilities of dbt Core. dbt Fusion is made available to customers and partners under the [dbt Product Licensing Agreement](https://www.getdbt.com/dbt-fusion-engine-license-agreement), which allows broad adoption subject to terms designed to support the sustainable business of its developer and maintainer (dbt Labs). - Other software is proprietary to dbt Labs and made available to customers and partners under commercial terms of service. This includes software that is available for free, within usage limits. *** ## Understanding dbt Core and dbt Fusion ### Has the license for dbt Core changed? No. There is no change in license for existing dbt Core software, or future releases of that software. dbt Core (which includes the dbt-core, dbt-common, and dbt-adapters repositories maintained by dbt Labs) is licensed under Apache 2, as it has been since its first release in 2016. As Fivetran + dbt Labs President Tristan Handy wrote in a [blog post introducing the dbt Fusion engine](https://www.getdbt.com/blog/new-code-new-license-understanding-the-new-license-for-the-dbt-fusion-engine), and again when [announcing Fivetran and dbt Labs’ merger](https://www.getdbt.com/blog/dbt-labs-and-fivetran-merge-announcement), the combined company will continue maintaining dbt Core under the Apache 2 license **indefinitely**. dbt Labs is committed to the ecosystem around dbt Core, and the thousands of users and customers who rely on it for their data work every day. ### Does a single shared engine mean dbt Core is being replaced? No. dbt Core is not: - a specific set of Python files. - the version of dbt you can run on a laptop. - the version of dbt you can run without paying. dbt Core is the completely open source implementation of the dbt framework. The dbt framework includes a language and an engine. The dbt **language**, the code you can write in your dbt project, has become a standard for the industry. dbt Labs has developed this language, with contributions and input from the community, in dbt Core over the past decade. The dbt **engine** is the foundational technology for compiling dbt projects, executing transformation graphs, and producing metadata. There is an entirely new next-generation engine for v2 of the dbt framework, written in a different programming language (Rust) than dbt Core v1.x (Python). Instead of maintaining two engines in two languages, dbt Labs has created a single engine which powers two distributions by open sourcing the code required to produce a Rust distribution of dbt Core v2. We are committed to maintaining and _continuing_ _to expand_ the dbt language across both the Core and Fusion distributions, exactly as we have done to date. You should expect to see new dbt Core versions (v2.1, v2.2, etc) that include support for new language features and fixes. dbt Labs will also continue to evaluate and integrate external contributions from the community. dbt Labs’ goal is to enable as many users as possible to upgrade to Fusion when they adopt version 2 of the dbt framework. We believe that Fusion will provide a superior development and deployment experience for everyone. You do not need to be a paying dbt customer to use Fusion. ### How is dbt Fusion licensed? The [dbt Product Licensing Agreement](https://www.getdbt.com/dbt-fusion-engine-license-agreement) terms only apply to the dbt Fusion binary and strike the balance of providing openness and flexibility for users, while also providing protections for dbt Labs to build a sustainable business as the software’s primary developer and maintainer. As a user of dbt Fusion, you can do almost anything with the software, except: - If you redistribute dbt Fusion to others as a managed service, you must permit your end users to utilize the full capabilities of dbt Fusion, including features gated behind login, if they choose to do so. User login must be accessible through standard documented flows. - You cannot circumvent dbt Fusion’s “license key” functionality or attempt to derive Fusion’s source code. - You cannot remove or obscure any notices about dbt Fusion’s license or dbt’s trademarks/copyrights. ### Why does dbt Fusion not use ELv2 any more? The primary purpose of the Elastic License (ELv2) is to prevent a tool’s use in competing products which host that tool as a service. Now that dbt Core v2.0 is built on the same engine – using code which was relicensed from ELv2 to Apache 2.0 – preventing competitive deployments of dbt Fusion is not a priority. Third party vendors can offer dbt Fusion as a managed service – including the advanced features which are available without login – provided they do not prevent users from logging in and enabling other premium features. This also aligns with the goals of [Open Data Infrastructure](https://www.getdbt.com/blog/dbt-labs-and-fivetran-product-vision), which at its heart prioritizes flexible tool choice, low switching costs, and interoperability with established standards. We would prefer users building on top of third-party tools (e.g. a different orchestrator) to adopt the full dbt Fusion binary, so they can seamlessly opt into additional services from dbt Labs in the future if they choose to. ### What’s the difference between dbt’s public source code and binary distributions? The Core and Fusion distributions of dbt v2 are both derived from a single engine which is written in Rust, a compiled language. dbt Core’s source code is visible in [the dbt-core repository](https://github.com/dbt-labs/dbt-core), and also distributed as a compiled binary. You are welcome to read, compile, modify, and redistribute the visible source code and the accompanying dbt Core binary. Both are licensed under the Apache 2.0 license. dbt Fusion is based on the same Apache-licensed source code in the dbt-core repository, and also includes proprietary components for which the source code is not publicly viewable. These components add functionality, some of which is available to everyone, and some which is available exclusively to logged-in or paying customers (via license key). Our documentation site will make it clear when functionality requires the proprietary Fusion distribution. The dbt Fusion distribution is subject to the dbt Product Licensing Agreement as described above. The dbt language spec and adapter functionality are freely available in the dbt-core repository and do not require a license key. ### What is the “license key” within the context of dbt Fusion? Some of dbt Fusion’s premium features are proprietary functionalities that are available only to registered or paying customers, and are unlocked via a license key. dbt Fusion’s license key is implemented via authentication with dbt Labs’ commercial software. By authenticating, users unlock these additional features. The dbt Product Licensing Agreement prohibits any attempt by any user to circumvent license key functionality. ### Does dbt Labs welcome contributions to dbt Core and dbt Fusion? Yes! dbt Labs maintains many open-source software projects in public repositories on GitHub ([https://github.com/dbt-labs](https://github.com/dbt-labs)). Anyone can contribute code to any of these projects after signing our [Contributor License Agreement](https://docs.getdbt.com/community/resources/contributor-license-agreements). If you are a user of dbt Fusion, contributions you make to the dbt-core repository will apply to both distributions since they share the same underlying code. As always, we value the participation of the community, and will carefully review and evaluate external contributions. We also recognize that valuable contributions come in many forms: opening issues, commenting in discussions, answering questions from other community members, and contributing code to fix bugs or extend functionality. *** ## Can I use dbt Fusion? ### Examples by use case **My team is using dbt to develop, transform, and test data assets in my company's cloud data warehouse. Those data assets are powering real-time dashboards for our colleagues and embedded product experiences for our customers. Is this a permitted use of dbt Fusion?** Yes, this is permitted. We believe strongly in the “dbt way” of doing analytical work (which we’ve called the [ADLC](https://www.getdbt.com/resources/guides/the-analytics-development-lifecycle)), and we believe that upgrading to dbt Fusion will enable your team to do this work even more effectively. **I'm a contractor or consultant setting up dbt Fusion for my clients to use internally. Am I permitted to continue doing this? Am I subject to the limitations on redistribution?** Yes, this is permitted and is not considered redistribution of dbt Fusion, assuming each client’s deployment is standalone and they could control it directly if they wanted to. **I want to use dbt Fusion to transform my customers’ data into assets that power my application. The app shows Fusion data test failures directly to customers, as a way of alerting them to data quality issues in their source data systems. Am I permitted to continue doing this?** Yes, this is permitted, because your customers are not using a tool that embeds and redistributes dbt Fusion directly. Rather, your customers are accessing the data itself, which is transformed using dbt Fusion behind the scenes. **I’m building a general-purpose data preparation and analytics product. I provide my customers with data transformation workflows that are leveraging dbt Fusion without exposing the dbt Fusion login mechanism to my customers. Is this a permitted use?** No. If your customers are submitting code, configuration, or other inputs to data transformation workflows embedded in your product, and your product is powered by dbt Fusion, users must be able to create an account and login to enable dbt Fusion’s premium features directly. It does not matter whether your customers’ inputs happen via UI, API, prompts, or otherwise. However, you _can_ use dbt Core v2.x in any way you choose, or modify the code in the dbt-core repository to meet your needs. If you take this approach, you must still respect dbt Labs’ [trademark policy and brand guidelines](https://www.getdbt.com/brand-guidelines). If you would like to discuss your specific case, and the possibility of a negotiated commercial agreement for dbt Fusion, please reach out to us at license@dbtlabs.com. **I’m building a data product that provides functionality complementary to dbt. I provide my customers with a dbt Fusion integration as part of my hosted/managed service. Is this a permitted use?** Yes, provided you comply with the dbt Product Licensing Agreement. If your product integrates with documented APIs of dbt — such as by generating dbt code to write back to your customers’ projects, or by parsing metadata artifacts that your customer provides from their own self-hosted dbt Fusion deployment — this is permitted without reservation (and encouraged!). dbt Labs publishes [validation schemas](https://github.com/dbt-labs/dbt-jsonschema) and [artifact specifications](https://github.com/dbt-labs/schemas.getdbt.com) with Apache 2 licenses, which you may freely use as part of building your integration. If your product integration invokes dbt Fusion against customer projects as part of your hosted or managed service, this use is permitted as long as you comply with the Redistribution requirements in the dbt Product Licensing Agreement. For example, you cannot block a customer’s network access to dbt servers, because they must be able to enable premium functionality if they choose to do so. Please reach out to us at license@dbtlabs.com with any questions. ### Examples by deployment pattern **If I am self-hosting Airflow to run dbt Core for my own business today, can I start running dbt Fusion instead?** Yes. **If I am an end user of a hosted/managed service that provides dbt Core today, can they offer dbt Fusion to me directly as a feature of their service?** Yes. The hosted/managed service provider must not prevent you from enabling Fusion’s premium features if you choose to do so, but they may provide you with access to dbt Fusion (which has additional capabilities beyond dbt Core even if you do not log in). **If I am an end user of a hosted/managed service that provides dbt Core today and has not implemented native dbt Fusion support, am I in violation of the license if I install dbt Fusion directly?** No, this is not a violation of the license. As an end user of dbt Fusion, you are not subject to the limitations applied to redistributors of Fusion. If you are the provider of a hosted/managed service that might run dbt Fusion, or if you have a different question not answered here, we encourage you to contact us at license@dbtlabs.com. **If I currently deploy dbt Core in an airgapped environment with no external network access, am I allowed to replace it with dbt Fusion?** Yes. You are allowed to deploy dbt Fusion into any environment you choose, with any networking restrictions required by your business. The dbt Product Licensing Agreement only prevents a _third party_ from blocking your ability to enable Fusion’s premium features if you choose to do so. **If I currently deploy dbt Core to developers across my company with preconfigured defaults which disable anonymous usage stats, am I allowed to replace it with dbt Fusion?** Yes. The Redistribution restrictions in the dbt Product Licensing Agreement only apply to those providing dbt Fusion to third parties. --- --- title: "Partners" description: "Join our partner ecosystem to deliver modern data solutions and empower analytics teams with dbt." url: "https://www.getdbt.com/partners" --- # Become a dbt Labs partner today Gain insider resources and unique opportunities while helping customers get the most from dbt. [Become a partner](https://partners.getdbt.com/) | [Find a partner](https://www.getdbt.com/partner-directory) *** ## Let's advance analytics engineering together dbt is the market leading solution that helps teams transform, document, test, and standardize their data. We partner with top data consultancies to ensure our customers get the most value from dbt. The dbt technology partner ecosystem consists of top-tier providers across data infrastructure and workflow solutions that complement and extend dbt’s capabilities. *** - Expand your community - Grow with us - Develop your team *** ## Technology Partners dbt Labs partners with innovative technology providers that advocate for the modern data stack and use dbt to deliver analytics engineering workflows, including the underlying data platforms to which dbt deploys. [Become a partner](https://partners.getdbt.com/) *** ## Consulting Partners dbt Labs Consulting Partners provide strategic support, technical implementation, ongoing development, and training to our customers so they can get the most value out of dbt. [Become a partner](https://partners.getdbt.com/) --- --- title: "Pricing" description: "Free Developer plan. Starter at $100/seat/month. Custom Enterprise options. Transparent pricing for every team size." url: "https://www.getdbt.com/pricing" --- ## dbt pricing ### Developer — Free For individual developers getting started with dbt, without managing infrastructure. - One Developer seat - 3,000 successful models built per month - 1 project **Features:** - Browser-based IDE - Multi-factor authentication (MFA) - Job scheduling and monitoring - CI checks on Github and GitLab - Upgrade to the latest dbt release automatically [Get started](https://www.getdbt.com/signup) ### Starter — $100 per user/month For teams collaborating on their first dbt project. - Five developer seats - 15,000 successful models built per month - 5,000 queried metrics per month - 1 project **Features:** - All features in Developer, plus: - Lineage with dbt Catalog - Define & query metrics with dbt Semantic Layer - dbt Semantic Layer basic - API access [Start a trial](https://www.getdbt.com/signup) ### Enterprise — Custom pricing For organizations scaling data collaboration and governance. - Custom Developer seat count - 100,000 successful models built per month - 20,000 queried metrics per month - 30 projects **Features:** - All features in Starter, plus: - Column-level lineage in dbt Catalog - Governed metrics with caching - Multi-project architecture (dbt Mesh) - SSO, Role-Based Access Control, and SCIM provisioning - Priority suport with SLAs [Contact sales](https://www.getdbt.com/contact) ### Enterprise+ — Custom Pricing For complex deployments requiring advanced security and control. - Custom Developer seat count - 100,000 successful models built per month - 20,000 queried metrics per month - Unlimited projects **Features:** - All features in Enterprise, plus: - PrivateLink - IP Restrictions - Run dbt in your own environment (Hybrid Projects) [Contact sales](https://www.getdbt.com/contact) *** ## Add-ons: pay only for what you use No seats, no minimums. Buy separately and run against self-hosted dbt, or add to a dbt platform plan. [View rates and billing details](https://www.getdbt.com/legal/service-consumption-table). *** ## dbt FAQs Frequently asked questions about how to get up and running using dbt. ### What kind of support do you offer? The global dbt Support team is available to dbt customers by email or in-product live chat. Developer and Starter accounts offer 24x5 support, while Enterprise customers have priority access and options for custom coverage. Additionally, Enterprise plan customers receive implementation assistance, dedicated account management, and a dbt Labs Security and Legal review. ### What does the free trial include? If you’re not sure which plan is right for your team, the 14-day fully-featured free trial of dbt is a great place to start. It allows your team to develop, test, document, and deploy SQL-based data transformations from the dbt UI. Once your 14-day free trial is up, you can either continue for free on the Developer plan (which provides dbt access for a single developer but does not include API access), or upgrade to the Starter or Enterprise plan. ### Will I have access to the dbt Community Slack? Yes! The [dbt Community Slack](https://www.getdbt.com/community/join-the-community) is home to thousands of analytics professionals, and commands significant attention from our dedicated dbt Community team. You’ll find channels like #advice-dbt-for-beginners, dedicated channels for users of various warehouses + BI tools, and groups for analytics leaders (#leading-data-teams, #analytics-craft). The dbt Community Slack is also where all attendees of our annual analytics engineering conference, [dbt Summit,](https://www.getdbt.com/dbt-summit) connect during the event. ### I’m new to dbt, how should I get started? Many users of all skill levels begin developing their first transformation within minutes of connecting their warehouse by following the [getting started tutorial](https://docs.getdbt.com/tutorial/setting-up). For a structured introduction, our free [dbt Fundamentals](https://learn.getdbt.com/courses/dbt-fundamentals) course covers everything you need to know to model, test, document, and deploy your first project. If your data team is looking for a more interactive experience, we also offer [in-depth “classroom” training](https://www.getdbt.com/dbt-learn/) to Enterprise customers: - Rapid Onboarding: Jumpstart your dbt implementation using your own data - Group Training: Build skills and confidence with sample data in a sandbox environment Additionally, [dbt Community Slack](https://www.getdbt.com/community/), the [dbt docs hub](https://docs.getdbt.com/) and the [developer blog](https://docs.getdbt.com/blog) are excellent resources for self or peer-to-peer education. ### Do I need to be comfortable working on the command line to use dbt? No! dbt includes an integrated development environment (IDE) with “git-guardrails” that allow you to start safely building and deploying dbt models without setting up your local machine or working on the command line. *** ## Billing and security FAQs Frequently asked questions about dbt plans, pricing and billing. ### How does billing work? Starter plans are billed monthly on the credit card used to sign up, based on developer seat count ($100USD per seat per month) and successful models built (over 15,000 per month). You’ll also be sent a monthly receipt to the billing email of your choice. If you’d like to change any billing information, just reach out to us at support@getdbt.com. Enterprise plan customers are billed annually based on the number of developer seats and successful models built, as well as any additional services + features in your chosen plan. ### Can I pay by invoice? At present, dbt Starter plan payments must be made via credit card, and by default they will be billed monthly based on the number of developer seats. We don’t have any plans to do invoicing for Starter plan accounts in the near future, but we do currently support invoices for companies on the dbt Enterprise plan. Feel free to [contact us to build your Enterprise pricing plan](https://www.getdbt.com/contact/). ### Can I upgrade or downgrade my plan? ​​Yes, you can upgrade or downgrade at any time. Account Owners can access their dedicated billing page via the account settings page: just click the hamburger icon and “Billing” to adjust your plan or update credit card information. If you’re not sure which plan is right for you, get in touch and we’ll be happy to help you find one that fits your needs. ### What if I want to cancel my account? You can cancel your account at any time on your Account Settings page. Of course, we’d hate to see you go – drop us a line and we’ll do everything we can to make it right! ### Does dbt store my data? dbt stores the following data persistently: - dbt account information including job definitions, database connection information, users, etc. dbt account information does not include any raw data from your warehouse. - Logs associated with jobs and interactive queries you’ve run. - Your dbt “assets” which include artifacts like run_results.json and manifest.json. Logs and assets do not include raw data from the warehouse, unless the code you write commands it. For example, it’s possible to write dbt code that fetches all customer data from your customer table and writes it to the logs. While that’s usually not a good idea and we do not recommend it, if you did that it’d mean that information is stored in dbt. ### How is data processed by the dbt IDE? When writing interactive queries from the IDE (for example: `select * from customers limit 100`) the resulting query output passes through dbt Cloud infrastructure on the way to your browser. However, this data is not persisted in any way (caching or otherwise). It does not live on our servers outside of your browser session. ### Are there other account parameter limits aside from those mentioned above? There are other limitations that most clients are unlikely to encounter, depending on client usage patterns. Truly “unlimited” usage of current and/or future features, products or services is never possible because costs, expenses, and supplier charges are subject to fluctuation and/or inflationary or other permanent increases. Client usage must remain subject to other reasonable use limitations. dbt Labs reserves the right to adjust limits, encourage optimization or increase pricing dependent on market forces, client usage patterns, and, ultimately, its discretion. --- --- title: "Solutions - AI" description: "Leverage AI with dbt to enhance data workflows, automate complex tasks, and gain predictive insights." url: "https://www.getdbt.com/product/ai" --- # AI runs on data. ||Data runs on dbt. dbt delivers the structured context and trusted standards your AI systems demand—ensuring fully governed, consistent outputs every time. [Build your AI pipeline](https://www.getdbt.com/signup) | [Talk to an AI expert](https://www.getdbt.com/contact) *** ## Don’t let messy data foundations hold your AI back. Without a standardized foundation, teams waste time reinventing how data is structured, governed, and queried for every AI system—resulting in slower outputs, inconsistent answers, and brittle workflows that don’t scale. - Lack of trusted, governed data for AI models - High risk of inaccurate models and unreliable predictions - Difficulty scaling data infrastructure for AI *** *Why dbt* ## Build your AI strategy on data you can trust. All AI systems thrive on standardized data. dbt’s unified framework provides the consistent metrics, rich context, and automated workflows your entire AI portfolio demands to execute reliably at scale. ### Redefine your data engineering Use dbt Copilot to change how data engineering is done and focus on the data work that matters most ### Stop AI misfires with trusted business context dbt provides AI systems with semantic context that enables them to make decisions aligned with your company's unique metrics and definitions ### Quickly trace, test, and fix AI data issues With a testing framework that catches data quality issues before they reach your AI systems, dbt eliminates lengthy troubleshooting cycles for your team ### One standard to power every AI tool Teams only have to plug into the dbt MCP server once to enable any AI system discover, query, and execute with confidence and speed *** ### dbt MCP server **Easily power any AI tool with trusted data** With the dbt MCP server, teams connect once to discover, query, and execute—instead of rebuilding logic and metadata for each AI agent and workflow ### dbt Semantic Layer **Let AI speak your business language** dbt creates a single source of truth for metrics and logic, generating fast, optimized SQL across multiple sources. AI systems query directly through the dbt Semantic Layer, ensuring consistent, governed decisions ### dbt Copilot **Deliver AI-ready data, faster** dbt Copilot accelerates development by generating context-aware SQL, tests, and documentation—all powered by your dbt project. It understands your models, so you can deliver trusted data with less time spent on boilerplate ### Orchestration & governance **Trust what your AI is built on** dbt automates scheduling of data transformations, enforces access controls, and enables collaboration—creating the operational backbone for reliable data pipelines that feed AI systems with fresh, trusted data on schedule *** [Watch video](https://youtu.be/fJ-72qOA7BE) *** *The foundation for reliable AI* ## Fuel your AI systems with structured context AI is only as reliable as the data it runs on. The dbt MCP server gives your AI agents and copilots direct access to structured, governed, version-controlled data. No brittle APIs, no duplicated logic. Define once, deploy everywhere: discover, query, and execute dbt projects with one connection. *** ## Trusted by teams building the future of AI. ### Rebtel improves data quality and data team productivity by migrating from Matillion to dbt Cloud > “Before, we couldn’t kick off any machine learning projects because incidents would happen. We had little visibility on our data lineage and code on Matillion, so we never really knew if the data was correct or complete. Now we’re working on an ML fraud prevention use case which will have a direct impact on our profit margins.” [Read more](https://www.getdbt.com/case-studies/rebtel) ### WHOOP improves efficiency by implementing dbt Core and migrating to dbt Cloud > “Access to accurate data is critical, it allows us to improve the customer experience and increase retention, lifetime value, and profitability.” [Read more](https://www.getdbt.com/case-studies/whoop) ### M1 Finance > For our business needs, our investment in AI and dbt Semantic Layer has been worth it. [Read more](https://www.getdbt.com/case-studies/m1-finance) *** ## Join the largest community shaping data & AI. The dbt Community is your gateway to best practices, innovation, and direct collaboration with thousands of data leaders and AI practitioners worldwide. Ask questions, share insights, and build better with the experts. [Join the Community](https://www.getdbt.com/community) *** *Learn more* ## Dive deeper into AI with dbt. Explore how dbt supports AI use cases from architecture to implementation. ### Understanding data governance for AI [Read the blog](https://www.getdbt.com/blog/understanding-data-governance-ai) ### Why your AI will fail without a semantic layer [Read the blog ](https://www.getdbt.com/blog/why-your-ai-will-fail-without-a-semantic-layer) ### Developing a modern data strategy for AI [Read the blog](https://www.getdbt.com/blog/modern-data-strategy-ai) *** ## Trusted globally. Proven at scale. ### 97% customer satisfaction Rated 4.9/5 on G2 by thousands of data leaders who trust dbt for critical analytics and AI initiatives. ### Enterprise-grade compliance ### Named a Leader by Snowflake and Databricks Recognized as Snowflake Data Integration Partner of the Year, and Databricks Customer Impact Partner of the Year ### 80,000+ teams Over 80,000 teams worldwide rely on dbt, processing billions of data transformations with confidence *** *Get started* ## Accelerate your AI initiatives today. Get a personalized demo and see how dbt empowers your data team to deliver trustworthy AI at scale. [Request your demo](https://www.getdbt.com/contact) | [Learn more about dbt](https://www.getdbt.com/product/dbt) --- --- title: "Analyst" description: "Enable analysts to build, explore, and share trusted data assets using dbt’s intuitive, AI-assisted tools within a fully governed environment." url: "https://www.getdbt.com/product/analyst" --- # From question to answer in one governed, AI-powered workflow. dbt empowers analysts to build, explore, and share trusted data assets through intuitive, AI-powered self-service — all within a fully-governed environment. [Request your demo](https://www.getdbt.com/contact) | [Get started for free](https://www.getdbt.com/signup) *** ## dbt powers trusted data at scale for the world's largest companies - Affirm - Nasdaq - Canva - Duolingo - TaskRabbit - GitLab *** [Watch video](https://youtu.be/pO_TUnCt6es) *** *Collaborate without compromise* ## Empower analysts to transform data Explore, transform, and model data - without writing SQL from scratch. dbt Canvas brings analysts into the fold with an AI-assisted visual workspace that’s fully governed. [See how Okta empowers analysts with dbt](#how-okta-empowers-analysts-with-dbt) *** *Don't get held back* ## Analytics is stuck in tabs, silos, and endless wait times. Analysts need answers fast but are blocked by engineering bottlenecks or ungoverned point solutions. The result is tab-switching, rework, and unreliable insights. dbt replaces this with a governed, AI-powered workflow that helps teams move faster — with confidence. *** ## Move from discovery to insight, faster. With dbt, analysts work alongside data teams using the same trusted standards where they can build, explore, and share, no matter their technical level. The result is faster decisions, fewer bottlenecks, and reliable insights. ### Discover trusted data Analysts can find what they need and trust what they find with dbt Catalog, helping them explore and understand data across sources in one governed place ![Screenshot of dbt Cloud’s catalog search feature, showing filtered results for “customer” across production environments in Snowflake and dbt, with metadata and last run timestamps.](https://cdn.sanity.io/images/wl0ndo6t/main/0ad9fad5e6078cb7a0f4dbd966e62ffa71029411-1224x1224.png) ### Build with confidence Visually build and refine data models with dbt Canvas, on AI-assisted, low-code interface for analysts ![Data flow diagram showing a left join between stg_users and stg_user_emails tables, followed by an aggregation step with two calculated metrics.](https://cdn.sanity.io/images/wl0ndo6t/main/919b7808c616056552fbb55ad30dee3b08ccc90e-1224x1224.png) ### Get insights fast From curiosity to clarity-dbt Insights lets analysts query, validate, and share insights without switching tools ![UI screenshot of a “Bookmarked queries” panel in dbt Cloud, showing saved SQL queries with names, descriptions, and last opened dates for quick access to analysis.](https://cdn.sanity.io/images/wl0ndo6t/main/91cd682b4a057fa52210ec0973e2d1dc9cf16938-1224x1224.png) ### Share and collaborate Work better together by sharing, exploring, and building insights in one secure, trusted space ![Example of using dbt Copilot to ask a data question—“What order items were most popular this year?”—showing the generated SQL query, quick execution time, and a table of results with product names and order counts.](https://cdn.sanity.io/images/wl0ndo6t/main/01771cf27b31a43a1f24f9343d5a5bf82c60feea-1224x1224.png) *** *AI-powered self-service tooling* ## Build, explore, and analyze without bottlenecks. Whether it's a last-minute request, an ad-hoc query, or a new KPI validation, analysts can pull the data they need, trust what they find, and move forward—without relying on engineering. ### Build your first model with a drag-and-drop interface ### Find and verify assets across sources, instantly ### Query and visualize without leaving dbt ### Validate a metric in natural language *** ## Governed, without the gatekeeping. Built for production on trusted, tested, and open standards—so everything analysts create is secure, scalable, and ready to ship. *** > > > — Tony Mayer > > > — William Tsu, Whoop *** ## One platform, one workflow. Collaborate seamlessly, build on trusted data, and move faster together in one platform. *** ## Context-aware AI to power self-service. Draw from tested models, metadata, and lineage to guide AI-powered workflows *** [Watch video](https://www.youtube.com/watch?v=iTECDGjJnh0) *** ## How Okta empowers analysts with dbt Okta, the world’s leading identity company, relies on dbt to power fast, trusted, and reliable decision-making across the business. By implementing dbt, Okta achieved: - Robust governance across data pipelines - Scalable self-service for analysts - Faster time to insights with less friction between teams *** ## Effortlessly integrate with the tools analysts already love. dbt connects with your existing BI tools, data warehouses, and analytics platforms. Instantly query, visualize, and share your governed data insights within familiar workflows. - Tableau - Power BI - Looker - Snowflake - Azure AI - Databricks *** ## Connect with a thriving community of analysts. Collaborate to solve difficult problems, share best practices, and accelerate your analytics skills as part of the dbt Community. With the most engaged analytics community in data, you'll never have to work alone. [Join the Community](https://www.getdbt.com/community/join-the-community) | [Explore Community resources](https://www.getdbt.com/community) *** *Dive deeper* ## Explore resources tailored for analysts. ### Read how dbt Canvas empowers analysts ### How analysts at JetBlue improved data trust and delivery by 95% ### Streamline dashboards with the dbt Semantic Layer *** *Get started* ## Transform your analytics workflow today. See firsthand how dbt empowers analysts with AI-powered, governed workflows. Request a demo or start your free trial now. [Request a demo](https://www.getdbt.com/contact) | [Start your free trial](https://www.getdbt.com/signup) --- --- title: "Solutions - Data Quality & Trust" description: "Build trust across your org with tested, versioned, and governed data powered by dbt’s transformation and observability tools." url: "https://www.getdbt.com/product/build-trust-in-data-and-data-teams" --- # Query your data—don't question it. Power your AI and data development with high quality, trusted data. [Build trust in your data](https://www.getdbt.com/signup) | [Talk to an expert](https://www.getdbt.com/contact) *** ## Establish real trust in your data quality. Poor data quality remains one of the greatest challenges to implementing successful AI and analytics projects. The best data teams build trust right into their data pipelines. ### Mature your analytics practice Easily build repeatable, documented, and transparent workflows that follow Analytics Development Lifecycle (ADLC) best practices to drive data trust at scal ### Deliver reliable data your whole org trusts Centralize metrics, maintain quality standards, and understand dependencies, so you consistently deliver high-value data products ### Embed data trust signals anywhere you work See data quality and freshness signals on your business-critical BI dashboards, and dig into detailed, column-level lineage via dbt Catalog ### Prevent data quality issues before they occur Resolve data quality issues before they hit production with version control, CI/CD, and observability and testing ### Build trusted AI on trustworthy data Reduce hallucinations and improve the reliability of your LLMs by training on high-quality data that includes the rich business context provided by dbt *** *Why dbt* ## Make data quality a cornerstone of your analytics and AI strategy. Slow response times, unreliable dashboards, and inconsistent results will frustrate any data-driven decision maker and may lead them towards ungoverned, expensive alternatives. That's why thousands of companies rely on dbt to restore trust in their analytics process. ### Proactive error prevention Catch and fix quality issues before pipeline changes are deployed, reducing debugging time and avoiding downstream problems ### Enhanced stakeholder trust Build confidence among business stakeholders and data practitioners through comprehensive quality checks and visible trust signals ### Standardized quality framework Implement automated testing, monitoring, and data health checks to ensure consistent data quality across the organization ### End-to-end data visibility Provide comprehensive data lineage tracking and quality metrics, allowing teams to quickly identify and resolve any data quality issues *** ### dbt Semantic Layer Create a centralized hub for managing key business metrics, ensuring consistency and accuracy across the organization ![dbt Semantic Layer](https://cdn.sanity.io/images/wl0ndo6t/main/1d47af5f4775d3b0c8ffb2217a29c85745470ed2-1224x1224.png) ### dbt Catalog Get visibility into data quality metrics, freshness indicators, and usage patterns through comprehensive metadata and detailed, column-level lineage ![dbt Catalog](https://cdn.sanity.io/images/wl0ndo6t/main/f0dae72e33ed350d7dc97ed094f3fc1d07631322-1224x1224.png) ### dbt Copilot Build high-quality data products faster with your context-aware AI assistant. Quickly generate models, documentation, tests, and more from metadata in your dbt projects. ![dbt Copilot](https://cdn.sanity.io/images/wl0ndo6t/main/1a8f2e3ded71f528a499b38aadfc927decc1435d-1224x1224.png) *** ## Trusted by teams that trust their data quality. ### Rocket Money modernizes financial reporting with dbt Cloud > "Having this automated Quote-to-Cash system run in dbt with our test suite allows us to confidently and quickly close our books each month." [Read more](https://www.getdbt.com/case-studies/rocket-money) ### Bilt Rewards saves 80% in analytics costs with the dbt Semantic Layer > “By centralizing our entity relationships in the dbt Semantic Layer, where all of our data transformations already live, we could easily create visualizations in our B2B product. We delivered an improved data experience for our B2B partners by eliminating a step in our process, decreasing our data costs by 80%, and increasing reliability and trust.” [Read more](https://www.getdbt.com/case-studies/bilt-rewards) ### Purple builds data trust with dbt Cloud > “dbt Cloud has been a game-changer in the way we handle data, bringing efficiency and reliability to our processes.” [Read more](https://www.getdbt.com/case-studies/purple) *** *The dbt Community* ## Join the largest community shaping data & AI. The dbt Community is your gateway to best practices, innovation, and direct collaboration with thousands of data leaders and AI practitioners worldwide. Ask questions, share insights, and build better with the experts. [Join the Community](https://www.getdbt.com/community/join-the-community) | [Explore the Community](https://www.getdbt.com/community) *** *Why teams trust dbt* ## Trusted globally. Proven at scale. ### 80,000+ teams using dbt dbt powers trusted analytics workflows and data at scale for the world's largest companies ### 97% customer satisfaction Rated 4.9/5 on G2 by thousands of data leaders who trust dbt for critical analytics and AI initiatives. ### Built with leading partners ### 100K+ Community members Join the largest open data community sharing best practices and building better data products *** *Learn more* ## Dig deeper into data quality & trust with dbt. See the ways dbt takes your data stack further. ### Manage data complexity at scale With dbt, data leaders can spearhead a unified approach for working with data that ensures quality and consistency. ### AI-ready data Build your AI initiatives on trustworthy data ### Choose a data quality framework Basic data hygiene techniques, such as testing, play a huge role in improving data quality. However, writing a few tests isn't enough. *** *Get started* ## Start building with dbt. Streamline your data transformation process, reduce manual errors, and increase productivity with dbt. Sign up today an take your data transformation workflow to the next level. [Request your demo](https://www.getdbt.com/contact) | [Start building trusted data](https://www.getdbt.com/signup) --- --- title: "Solutions - Cost Optimization" description: "Cut query costs and improve performance with dbt. Optimize spend and drive efficiency across your data workflows." url: "https://www.getdbt.com/product/cost-optimization" --- # Transform cost from overhead to opportunity. In today’s data economy, cost control is no longer optional—it’s strategic. dbt empowers data teams to move beyond reactive cost monitoring and into proactive, value-aligned data operations. Shift the narrative from “cost center” to “profit driver.” - **29%+ costs avoided** Save on compute costs with intelligent Fusion-powered model reuse that eliminates unnecessary processing. [Start cutting costs](https://www.getdbt.com/signup) | [Talk to an expert](https://www.getdbt.com/contact) *** ## Warehouse costs are rising — efficiency has to keep up. Modern data teams are building more, faster than ever before. This growth comes with increasing complexity—and ballooning warehouse spend. - Teams need tools to tame cost - Your team doesn't always get to scale *** ### Avoid: build with efficiency by default Reduce waste with incremental models that process only new or changed data. Streamline orchestration with Fusion powered [dbt State](https://www.getdbt.com/product/dbt-state) workflows to eliminate redundant queries. Smart defaults like CI, defer, and model selection help ensure every run is optimized for cost. ![Avoid: Build with efficiency by default](https://cdn.sanity.io/images/wl0ndo6t/main/482ea632441f0eef76a9a5f2f389ccbe7cde9d96-1224x1224.png) ### Remediate: fix cost issues Take action where transformation happens: fix issues directly in dbt using code, not tickets. ![Image](https://cdn.sanity.io/images/wl0ndo6t/main/71926d421915cec51ed893e8bf1eedf27d2e4b06-1224x1224.png) *** > > > — James Dorado, Bilt Rewards *** ## Before dbt - Redundant queries - Developer time wasted on reactive debugging - Budget overages and unclear ROI *** ## With dbt - Queries built and executed efficiently - Automated cost-awareness in dev workflows - Clear linkage between cost and value *** ## See how leading orgs optimize costs with dbt ### Symend implements a robust data foundation fit for scale with dbt Cloud > “I fell in love with dbt when we were decreasing data latency. We were previously doing full loads, twice a day, and runs took a full 12 hours. We implemented an incremental solution with dbt that significantly increased Snowflake's speed so we could get latency down to two hours." [Read more](https://www.getdbt.com/case-studies/symend) ### Bilt Rewards saves 80% in analytics costs with the dbt Semantic Layer > “By centralizing our entity relationships in the dbt Semantic Layer, where all of our data transformations already live, we could easily create visualizations in our B2B product. We delivered an improved data experience for our B2B partners by eliminating a step in our process, decreasing our data costs by 80%, and increasing reliability and trust.” [Read more](https://www.getdbt.com/case-studies/bilt-rewards) ### Enpal fuels data efficiency with dbt and saves 70% on data costs > “We used to have outages on a regular basis where the organization wouldn’t have updated data for a whole day. This year, we’ve only had three or four minor hiccups that we could fix in a few hours.” [Read more](https://www.getdbt.com/case-studies/enpal) *** *The dbt Community* ## Join the largest community shaping data The dbt Community is your gateway to best practices, innovation, and direct collaboration with thousands of data leaders and AI practitioners worldwide. Ask questions, share insights, and build better with the experts. [Join the Community](https://www.getdbt.com/community/join-the-community) | [Explore the Community](https://www.getdbt.com/community) *** *Why teams trust dbt* ## Trusted globally. Proven at scale. ### 80,000+ teams using dbt dbt powers trusted analytics workflows and data at scale for the world's largest companies ### 97% customer satisfaction Rated 4.9/5 on G2 by thousands of data leaders who trust dbt for critical analytics and AI initiatives. ### Built with leading partners ### 100K+ Community members Join the largest open data community sharing best practices and building better data products *** *Learn more* ## Dig deeper into optimizing your business costs with dbt. ### Save 29% by using state-aware orchestration With state-aware orchestration enabled, dbt moves from being stateless to stateful. Instead of simply running exactly what was specified in a job, dbt maintains a real-time fingerprint of both model code and data state. ### From cost center to profit driver: How modern teams optimize data costs. You can turn your data team from a cost center into a revenue engine—just start here. Check out our on-demand webinar to learn how top data leaders are shifting from cost center to strategic growth engine, and how you can too. ### Achieve a 194% ROI with dbt Download the study to learn how you can improve trust in your data by helping teams move beyond outdated stored procedures or drag-and-drop tools that are less transparent and approachable than modern approaches. ### Build the business case for dbt Get real-world strategies from dbt users, insights from the latest State of Analytics Engineering report, and expert advice to help you successfully adopt and scale dbt. *** *Get started* ## Start building with dbt. Streamline your data transformation process, reduce manual errors, and increase productivity with dbt. Sign up today an take your data transformation workflow to the next level. [Request your demo](https://www.getdbt.com/contact) | [Optimize your spend](https://www.getdbt.com/signup) --- --- title: "Solutions - Data Modernization" description: "Eliminate bottlenecks, enhance governance, and scale analytics with dbt’s modular, cloud-native platform." url: "https://www.getdbt.com/product/data-modernization" --- # Modernize your approach to data. Update more than just your technology—advance to a truly modern data strategy. [Request your demo](https://www.getdbt.com/contact) | [Explore dbt for data modernization](https://www.getdbt.com/product/dbt) *** ## Eliminate pipeline bottlenecks with modern transformations Non-standard transformations bury logic in hard-to-access code, making it nearly impossible for AI and analytics teams to understand, trust, or quickly use the data they need *** - Future-proof your data development process - Embrace agile data strategies *** - Improve cross-functional collaboration - To achieve scale, don't recreate—reuse *** *Why dbt* ## Work with the new best practices for data. Modernize your data development process with strategies supported by dbt. With a focus on how data is transformed, instead of just the tools you use, you can redefine how your team delivers data. ### Upgrade to the cloud Move smoothly into a modern, cloud-based workflow using one platform that manages all downstream components ### Optimize for governance Give your team an end-to-end understanding of data dependencies across workflows ### Improve cost efficiency Make the most efficient use of your cloud warehouse resources, regardless of workload volume or variety ### Enhance data quality Follow analytics development best practices to ensure analytics and AI outputs are built on top of high-quality, trusted data *** ### dbt Canvas Broaden participation in governed data development through a visual drag-and-drop interface for creating and editing dbt models ![dbt Canvas](https://cdn.sanity.io/images/wl0ndo6t/main/d384263b9fe7aa460797f3d181fe2f98d378e778-1224x1224.png) ### dbt Copilot Automate routine tasks and improve data quality with an AI-powered assistant that auto-generates SQL, documentation, semantic models, and tests ![dbt Copilot](https://cdn.sanity.io/images/wl0ndo6t/main/482ecf1ed430fd6f853d19ba7114e5ab984cc984-1224x1224.png) ### dbt Catalog Visualize dependencies, trace data lineage, and optimize performance—so you can spend less time untangling pipelines and more time delivering value ![dbt Catalog](https://cdn.sanity.io/images/wl0ndo6t/main/d8514d11fbcd68ec0518a8d4aee081d2446919c9-1224x1224.png) *** ## See dbt in action ### JetBlue eliminates data engineering bottlenecks with dbt > "The new workflow with dbt and Snowflake isn't a small improvement. It's a complete redesign of our entire approach to data that will establish a new strategic foundation for analysts at JetBlue to build on." [Read more](https://www.getdbt.com/case-studies/jetblue) ### Nasdaq empowers business users with dbt Cloud and a modern data stack > “Before, 9 out 10 times the sales and executive team had to wait months to receive a data point they requested. By then, the data wasn’t relevant anymore or the new business was already lost.” [Read more](https://www.getdbt.com/case-studies/nasdaq) *** *The dbt Community* ## Join the largest community shaping data The dbt Community is your gateway to best practices, innovation, and direct collaboration with thousands of data leaders and AI practitioners worldwide. Ask questions, share insights, and build better with the experts. [Join the Community](https://www.getdbt.com/community/join-the-community) | [Explore the Community](https://www.getdbt.com/community) *** *Why teams trust dbt* ## Trusted globally. Proven at scale. ### 80,000+ teams using dbt dbt powers trusted analytics workflows and data at scale for the world's largest companies ### 97% customer satisfaction Rated 4.9/5 on G2 by thousands of data leaders who trust dbt for critical analytics and AI initiatives. ### Built with leading partners ### 100K+ Community members Join the largest open data community sharing best practices and building better data products *** *Learn more* ## Dig deeper into data modernization with dbt ### How CHG Healthcare modernized their data stack Discover how CHG Healthcare streamlined data delivery and empowered business users with faster, more reliable insights. ### A modern data strategy for the Age of AI Explore how data leaders are rethinking architecture, governance, and agility to unlock AI-powered value. ### The future of the modern data stack Dive into what’s next for the MDS—shifting priorities, emerging patterns, and what it means for data teams today. *** *Get started* ## Start building with dbt. Streamline your data transformation process, reduce manual errors, and increase productivity with dbt. Sign up today and take your data transformation workflow to the next level. [Request your demo](https://www.getdbt.com/contact) | [Modernize your stack](https://www.getdbt.com/signup) --- --- title: "Product - Data Vault" description: "Streamline Data Vault 2.0 implementation using dbt’s templates, lineage tracking, and integrated testing for enterprise-scale agility." url: "https://www.getdbt.com/product/data-vault" --- # Manage enterprise-scale complexity with confidence. Maintain your mission-critical data pipelines and scale without breaking a sweat. [Book a demo](https://www.getdbt.com/contact) | [Sign up for free](https://www.getdbt.com/signup) *** ## Data teams around the world love dbt - Affirm - Nasdaq - Canva - Duolingo - TaskRabbit - GitLab - Hubspot - jetBlue - Air New Zealand - Thermo Fisher Scientific - Conde Nast - Vestas - Altis Consulting - Domain - New Relic - Anheuser-Busch Group - Hotelbeds - CHG Healthcare - Talkdesk - Virgin Media *** ## Large-scale development demands Data Vault and dbt Implement Data Vault with dbt for the best solution to managing complex data systems. It’s designed to support large-scale development and provides Enterprise-level support for your team. ### Ship changes faster Increase production with an intuitive development environment, automatic documentation, and built-in lineage. ### Build at maximum scale Use template-driven development to build and scale to over 5,000 Data Vault components. ### Elevate data quality Produce reliable data products with integrated testing at every step and code change management. *** ## Start easily with dbt packages for Data Vault Get started in no time with open source dbt packages like [AutomateDV](https://hub.getdbt.com/datavault-uk/automate_dv/latest/) and [datavault4dbt](https://hub.getdbt.com/scalefreecom/datavault4dbt/latest/). They provide all the standard Data Vault 2.0 features you need to build, with code created by expert practitioners. [Book a demo](https://www.getdbt.com/contact) | [Create a free account](https://www.getdbt.com/signup) *** ## See dbt in action Explore how dbt Labs has helped clients achieve better outcomes, increase efficiency, and grow their business with customer case studies. ### Siemens implements a data mesh architecture at scale with dbt Cloud > “Already in our first dbt Cloud project we were amazed by the seamless collaboration dbt Cloud offers, allowing us to effortlessly work together on the same Snowflake project. With built-in tests, simple job scheduling, and easy deployment, dbt Cloud enabled us to immediately focus on the business case rather than spending time on our data architecture setup.” [Read more](https://www.getdbt.com/case-studies/siemens) ### Nasdaq empowers business users with dbt Cloud and a modern data stack > “Before, 9 out 10 times the sales and executive team had to wait months to receive a data point they requested. By then, the data wasn’t relevant anymore or the new business was already lost.” [Read more](https://www.getdbt.com/case-studies/nasdaq) ### *** ## Start building with dbt Streamline your data transformation process, reduce manual errors, and increase productivity with dbt. Sign up today and take your data transformation workflow to the next level. [Book a demo](https://www.getdbt.com/contact) | [Create a free account](https://www.getdbt.com/signup) --- --- title: "Product - dbt" description: "Streamline data transformation with dbt. Automate workflows, boost collaboration, and scale with confidence." url: "https://www.getdbt.com/product/dbt" --- # The standard for AI on structured data. Rely on dbt to power your analytics workflows with trusted, AI-ready data. [Get started free](https://www.getdbt.com/signup) | [Talk to an expert](https://www.getdbt.com/contact) *** *See dbt in action* ## Change how you do data. Ditch silos and centralize your analytics workflows on a platform built for scale. Connect to any data platform and give your teams a shared foundation to translate raw data into analytics and AI-ready insights. *** [Watch video](https://youtu.be/N3ByqpVSGIM) *** ### Reduce platform costs Abstract business logic into a flexible platform and write and run code more efficiently to optimize every dollar of data platform spend ### Accelerate delivery Boost productivity with AI built into every part of the workflow. Clear bottlenecks, improve data literacy, and encourage governed self-service ### Build trust Deliver governed, observable data anywhere. Ensure quality, consistency, and cost-efficiency across the entire lifecycle—without slowing down *** *A scalable workflow* ## The Analytics Development Lifecycle — at scale. The ADLC is how mature teams build, govern, and scale their best data ideas. From initial planning to ongoing observability, dbt supports each step with purpose-built features and interfaces. [Learn more about the ADLC](https://www.getdbt.com/resources/guides/the-analytics-development-lifecycle) *** *dbt features* ## Platform experiences that span the analytics workflow. Explore the building blocks of the dbt platform that empower teams to bring the best ideas from software engineering into analytics and manage complexity at any scale. ### Transformation Build data models just by writing SQL, and keep pipelines flowing with version control and CI/CD [Learn more](https://www.getdbt.com/product/develop) ### Orchestration Automate end-to-end pipelines and deploy code with confidence [Learn more](https://www.getdbt.com/product/deploy) ### Observability Use proactive tests and built-in observability signals to resolve issues fast and maintain data health [Learn more](https://www.getdbt.com/product/test-and-observe) ### Catalog Visualize comprehensive lineage and dig into metadata to build context and improve data products [Learn more](https://www.getdbt.com/product/dbt-catalog) ### Semantic Layer Define consistent metrics and deliver them to any dashboard or LLM [Learn more](https://www.getdbt.com/product/semantic-layer) ### Mesh Manage complexity across teams and across data platforms with mesh architecture [Learn more](https://www.getdbt.com/product/dbt-mesh) *** *Next-gen engine* ## Meet Fusion: The new engine powering dbt. A brand new, lightning-fast engine is here. Experience faster performance, a hyper-responsive developer experience, and built-in cost efficiencies. [Explore Fusion](https://www.getdbt.com/product/fusion) *** *It's about outcomes* ## Standardize on the industry standard. Adopting dbt puts your organization on track to make data quality a foundational aspect of data and AI development. Collaborate from a common framework to deliver real business results without driving up costs. ### Improve data quality & trust Catch issues before they go live with built-in testing and observability, keep pipelines flowing with automated orchestration, and share data health signals anywhere ### Unify context Break down silos across warehouses, tools, and teams. Collaborate from a common foundation, with metadata as your connective tissue ### Enable scalable collaboration Bring more collaborators into the data workflow with accessible interfaces and governed inroads, all backed by a unified foundation *** ## across the data stack - BigQuery - Databricks - Fabric - Fivetran - Redshift - Snowflake *** ## Build better. Ship faster. From first model to federated data mesh — dbt is how modern data teams ship and scale trusted data. [Book a demo](https://www.getdbt.com/contact) | [Learn about the Community](https://www.getdbt.com/community) *** *Why teams trust dbt* ## Trusted globally. Proven at scale. ### 80,000+ teams using dbt dbt powers trusted analytics workflows and data at scale for the world's largest companies ### Top-rated on G2 Recognized in Gartner's DataOps Market Guide 2024 ### Built with leading partners ### 100K+ Community members Join the largest open data community sharing best practices and building better data products *** *Learn more* ## Get under the hood with dbt. Unpack what makes dbt so powerful for so many teams — from product fundamentals to architectural deep dives. ### Get to know the dbt data control plane See how dbt’s features help teams manage complexity at any scale. ### Learn more about the ADLC Mature your analytics practices in the age of AI ### Everything we announced at the 2025 dbt Launch Showcase Learn about the latest features powering dbt *** *Get started* ## Built trust, move faster, and cut costs. Discover how dbt works as your team’s control plane for trusted, scalable data. [Book a demo](https://www.getdbt.com/contact) | [Create your free account](https://www.getdbt.com/signup) --- --- title: "Capabilities - Discover" description: "Explore dependencies, trace lineage, and monitor performance across your data estate using dbt Catalog’s interactive interface." url: "https://www.getdbt.com/product/dbt-catalog" --- # Visualize and optimize your pipelines with dbt Catalog. dbt Catalog gives you a bird's-eye view of your data estate and the detailed context you need to deliver quality data. [Explore dbt Catalog](https://www.getdbt.com/signup) | [Talk to an expert](https://www.getdbt.com/contact) *** *The Analytics Development Lifecycle* ## Less untangling pipelines. More delivering value. dbt Catalog helps your team visualize dependencies, trace data lineage and optimize performance throughout the Analytics Development Lifecycle (ADLC). Learn how lineage tracking, usage insights, and performance monitoring help teams understand and improve their dbt projects—faster. [Read the ADLC whitepaper](https://www.getdbt.com/resources/the-analytics-development-lifecycle) *** *Why dbt Catalog* ## Boost your data insights with a self-generating knowledge base. dbt Catalog automatically creates metadata, documentation, and lineage for your data, allowing teams to easily explore the status and relationships of their data platform assets in a user-friendly interface. ### See all your context in one place Quickly find and view dependencies and metadata details of your team's data assets without leaving dbt ### Reuse—don't rebuild Increase productivity by letting developers easily discover and reuse existing assets ### Troubleshoot faster Save debugging time by tracing table- and column-level lineage to quickly spot and resolve issues *** ## Get the context you need to navigate and improve your data products. Align teams and optimize pipelines with a unified understanding. ### End-to-end lineage Automatically build and visualize your end-to-end lineage graph—from data source all the way to the dashboard or AI endpoint your models power—with detailed metadata into each node ![End-to-end lineage](https://cdn.sanity.io/images/wl0ndo6t/main/f612e4a29d0190a25080dfe64899f4152914bbf7-1224x1224.png) ### Global search Find the exact resource you're looking for, across projects and across your entire data platform, so you can manage complexity while keeping your code DRY ![Global search](https://cdn.sanity.io/images/wl0ndo6t/main/85a226ca331f4b15ddd52012ac8b212820aa6f5c-1224x1224.png) ### Lineage lenses Overlay parameters onto your DAG — like model execution status, column-level evolution, model query history, and more — to quickly intuit details that help you build more resilient, efficient pipelines and debug issues faster ![Lineage lenses](https://cdn.sanity.io/images/wl0ndo6t/main/c5a4eece7dd73881a846fa16f7bbef8f0c1b3983-1224x1224.png) ### Project recommendations Translate your project's metadata into actionable insights so you can proactively prioritize best practices like improving test and documentation coverage, and tend to project health to keep your pipelines humming ![Project recommendations](https://cdn.sanity.io/images/wl0ndo6t/main/c2158e82ae9ec7037c359f207849f4ae7da7a631-1224x1224.png) ### Health signals Build trust by embedding health signals like data freshness and data quality directly into stakeholder dashboards. See those same signals in dbt to stay on top of project maintenance ![Health signals](https://cdn.sanity.io/images/wl0ndo6t/main/a9568a87c34054aba8a0657a9786d47023ea818e-1399x1364.png) *** ## Build better with dbt today. dbt is how modern data teams ship and scale trusted data. [Book a demo](https://www.getdbt.com/contact) | [Explore dbt](https://www.getdbt.com/product/dbt) *** > > > — Robert Goodman, Lennar > > > — Katie Claiborne, Cityblock Health > > > — Rahavan Raman, Zscaler > > > — Gary How, Kenvue > > > — Shravan Banda, World Bank *** *Additional resources* ## Learn more about dbt Catalog Check out these resources to find out how dbt Catalog can help you deliver value. ### Become a dbt Catalog expert Learn five tips and tricks for getting the most out of dbt Catalog. ### Trace root cause with column-level lineage Learn more about how to use column-level lineage in dbt to spot and fix pipeline issues fast. ### Build a scalable data quality framework Learn about the various testing capabilities in dbt to build trust in data. *** ## Make discovery easy with dbt Catalog. Get the context you need to build resilient, trusted data pipelines. [Book your demo](https://www.getdbt.com/contact) | [Explore dbt](https://www.getdbt.com/product/dbt) --- --- title: "Capabilities - Plan" description: "Empower domain teams to own data pipelines while maintaining centralized governance and cross-project lineage with dbt Mesh." url: "https://www.getdbt.com/product/dbt-mesh" --- # Collaborate at any scale with dbt Mesh. Allow domain teams to own their projects while staying aligned with shared definitions, governance, and cross-project lineage. [Scale your data teams](https://www.getdbt.com/signup) | [Talk to an expert](https://www.getdbt.com/contact) *** *The Analytics Development Lifecycle* ## dbt Mesh creates the right foundation for your data lifecycle. Bring structure to how analytics work gets scoped and shared, making the rest of the lifecycle simpler, smoother, and better governed—from data development through to analysis. [Read the ADLC whitepaper](https://www.getdbt.com/resources/the-analytics-development-lifecycle) *** *Why dbt Mesh* ## Centralized governance, distributed access. As teams and data grow, so does the risk of duplication, misalignment, and quality incidents. By enabling federated ownership and enhancing observability, dbt Mesh gives organizations the tools to scale data collaboration without sacrificing quality or speed. ### Empower data teams Give your teams the freedom to own their data pipelines and use the data platform of their choice—without the bottleneck of a central team ### Centralize governance Enable your central data team to maintain visibility of end-to-end lineage and set global development standards ### Embrace flexible architecture Data organizations come in many forms. Work with data tools that fit your architecture—not fight against it *** ## Power governed collaboration. Features built to support federated teams working across multiple projects, data platforms, and domains. ### Cross-project references Seamlessly reference models from other dbt projects—or other data platforms—to avoid duplication and streamline development ![Visual example of cross-project references in dbt, showing how a ref function pulls from a product_analytics model to build a pendo_guide_event in the stg_customers model.](https://cdn.sanity.io/images/wl0ndo6t/main/a05ea7eaf3da5465e116a897718a008cd82de38d-1224x1224.png) ### Enhanced data governance Specify access levels for your dbt models, apply contracts to guarantee the shape of a model’s data, and use versions to provide downstream teams with smooth upgrade pathways ![Diagram showing unified data governance by linking multiple user datasets with key-based relationships into a central, controlled model.](https://cdn.sanity.io/images/wl0ndo6t/main/c41f92b34c111a4325b1e0a0e1aa831f53cbd610-1224x1224.png) ### End-to-end lineage across domains Trace data lineage across data domains and data platforms to ensure complete visibility into the provenance and impact of key data assets ![Visualization of end-to-end lineage across dbt Mesh projects—Platform, Finance, and Marketing—showing connected public models in a unified data workflow.](https://cdn.sanity.io/images/wl0ndo6t/main/f391820d433413c534797f22a8c61a3e0f29bbd3-1224x1224.png) ### Data platform flexibility Collaborate seamlessly, across one cloud data platform or many. Use dbt Mesh to connect projects across different platforms using the Apache Iceberg™ table format (coming soon) ![Diagram showing flexible model referencing across dbt projects, with Data Platform 2 using the ref function to pull from Data Platform 1’s stg_order_items model.](https://cdn.sanity.io/images/wl0ndo6t/main/7b3b24a1b45982faca5c53cadc6d097fe84589bd-1224x1224.png) ### Hybrid dbt deployments Connect upstream projects using dbt Core to downstream projects using dbt ![Illustration of a hybrid dbt deployment, connecting dbt Core’s data processing engine with dbt Cloud’s user interface, development tools, and collaboration features.](https://cdn.sanity.io/images/wl0ndo6t/main/7c1408ffdaad07bb9c002dd3c79fc72256f755ab-1224x1224.png) *** ## Less data work. More data that works. From first model to federated data mesh, dbt is how modern data teams ship and scale trusted data. [Book a demo](https://www.getdbt.com/contact) | [Explore dbt](https://www.getdbt.com/product/dbt) *** ## Trusted by the best in data. Leading organizations rely on dbt Mesh to build modular, governed, high-performing data ecosystems. ### Siemens implements a data mesh architecture at scale with dbt Cloud > “Already in our first dbt Cloud project we were amazed by the seamless collaboration dbt Cloud offers, allowing us to effortlessly work together on the same Snowflake project. With built-in tests, simple job scheduling, and easy deployment, dbt Cloud enabled us to immediately focus on the business case rather than spending time on our data architecture setup.” [Read more](https://www.getdbt.com/case-studies/siemens) ### WHOOP improves efficiency by implementing dbt Core and migrating to dbt Cloud > “Access to accurate data is critical, it allows us to improve the customer experience and increase retention, lifetime value, and profitability.” [Read more](https://www.getdbt.com/case-studies/whoop) ### Nasdaq empowers business users with dbt Cloud and a modern data stack > “Before, 9 out 10 times the sales and executive team had to wait months to receive a data point they requested. By then, the data wasn’t relevant anymore or the new business was already lost.” [Read more](https://www.getdbt.com/case-studies/nasdaq) *** *Additional resources* ## Dig into dbt Mesh and modular data architectures. ### Intro to dbt Mesh Learn more about dbt Mesh and explore best practices for deploying your own [Read intro](https://docs.getdbt.com/best-practices/how-we-mesh/mesh-1-intro) ### Quickstart with dbt Mesh Quickly set up your own multi-project architecture using the foundational concepts of dbt Mesh [Read guide](https://docs.getdbt.com/guides/mesh-qs?step=1) ### dbt Mesh FAQs Answers to any questions you might have about dbt Mesh [Read FAQs](https://docs.getdbt.com/best-practices/how-we-mesh/mesh-5-faqs) *** ## Start planning with dbt Mesh. Give your teams the autonomy they want—and the governance your organization needs. [Book your demo](https://www.getdbt.com/contact) | [Explore dbt](https://www.getdbt.com/product/dbt) --- --- title: "dbt State" description: "dbt State checks your metadata and model SQL on every run — building only what changed, skipping the rest. Cut warehouse compute & ship fresher data." url: "https://www.getdbt.com/product/dbt-state" --- # Build what’s changed, skip what hasn’t. dbt State builds only what has changed. Simplify orchestration, iterate faster in governed dev environments, and cut warehouse compute by 15-30%. Locally or in the cloud. [Get started](https://us1.dbt.com/register?_dbtsrc=dbt-state) *** *Why dbt State* ## Stop rebuilding. Start saving. Whether you're orchestrating in the dbt platform, running dbt locally, or using an external orchestrator, dbt State makes every run smarter: less compute, simpler orchestration, and faster iteration. ### Simplify orchestration Apply freshness on the model in code, not in the scheduler. Run as often as the business needs. No custom workflows, no manual orchestration. ### Develop faster with guardrails Start building in seconds without any complex setup rituals. Iterate freely and faster without fear of expensive mistakes or breaking changes. ### Optimize performance Reduce warehouse compute by 15-30% on average by only building models when upstream data or code has actually changed. Stop paying to rebuild what hasn't. *** > > > — Gordon Curzon, Virgin Media O2 *** *How it works* ## Intelligence built into every run. On every run, dbt State checks your metadata and model SQL to see what’s changed. When upstream data or code has changed, it **builds** the model. Otherwise, it **skips** the build by: - **Reusing **existing state — zero compute, zero risk - **Cloning** existing state with minimal compute cost - **Auto-deferring** (in development) to production state This works for full models, incremental models, snapshots, seeds, and tests. *** *In production* ## Simpler orchestration, fresher data, more efficient runs. Eliminate hours spent maintaining custom workflows and manual orchestration. Just turn dbt State on, configure freshness, and run your jobs as often as you need. That means fresher data, less complexity, and meaningful warehouse savings without changing how you work. **Tuned configurations. **Declare freshness and dependency rules directly in your project code. Set a max staleness window via lag_tolerance so models rebuild only when they're due — not every run. Move orchestration logic from imperative scheduling into declarative, version-controlled configurations. *** *In development* ## Iterate faster in governed dev environments. Not only does dbt State skip and clone models in development, but it can auto-defer to production state, so analytics engineers can start building immediately — no manual overhead and no fear of costly mistakes. Auto-clone from prod and auto-defer let you start building in seconds. Only run the part of the DAG you’re working on. No cloning macros, no staleness bookkeeping. No selection-syntax expertise needed; dbt State is a structural guardrail against runaway dev cost, no matter who, or which AI agent, runs the command. *** ## Run anywhere. Optimize everywhere. dbt State is available as a plugin for dbt Core or out-of-the-box in the dbt platform. Whether you run locally, with your own orchestrator, or on the dbt platform — you get the same efficiency. *** ## Reuse more, save more. dbt State pricing is usage-based. You pay based on the benefit from model reuse. dbt State cost is measured using Daily Active Target Tables. Daily active target tables (DATT) are measured as the number of distinct target tables for which dbt State performs a unique skip or clone, and unique test reuse operations on a given calendar day. **Visit the [pricing page](https://www.getdbt.com/pricing) to learn more.** *** ## Frequently asked questions ### Does dbt State work with dbt v1? Yes. dbt State is available as a plugin for dbt Core (1.7+). Install it, run dbt build, and you're optimizing immediately — no platform migration required. ### Does dbt State work with external orchestrators? Yes. Whether you run dbt through Airflow, Dagster, or any other orchestrator, dbt State works the same way. It evaluates state on every run regardless of how that run is triggered. *** ## Stop rebuilding unchanged models. Start saving today. Get started in minutes — whether you run dbt locally or in the dbt platform. [Get started](https://us1.dbt.com/register?_dbtsrc=dbt-state) --- --- title: "dbt Wizard" description: "dbt Wizard is grounded in your dbt project — lineage, compiled state, and metrics. Build, debug, and refactor with confidence." url: "https://www.getdbt.com/product/dbt-wizard" --- # Your personal dbt agent, available wherever you work. *** ## The AI agent built for the way analytics engineers work Generic coding agents don't understand your data. dbt Wizard is grounded in it: lineage, grain, compiled state, tests, and metric definitions. Available wherever your team or you develop. ### Knows your data, not just your code Natively understands your full dbt project, so every change comes with full context on what's upstream, downstream, and at stake — and shows you exactly how the logic changed in the DAG. ### Self-validates before you review An opinionated workflow makes validation the default, so problems get caught before they ship, not after. Fewer production incidents, less time fixing what AI got wrong. ### Governed and auditable by default Every change is auditable and nothing ships without review. Keep a human in the loop to always know what changed, why, and who approved it. ### Always calls the right tool With high-precision tool orchestration, Wizard knows exactly which dbt-specific call to make and when ### No context hunting. Less token waste. dbt's native metadata engine retrieves exactly what the agent needs before it writes a line, so you get more accurate output while optimizing token spend. ### Zero setup. Zero maintenance. No MCP infrastructure to configure, no DIY system to maintain, no per-model bills to manage — just cost-efficient access to the best models. Connect and start shipping. *** ## Join the Wizard Desktop private beta! Run complex builds side by side, each safely isolated, in one always-open app. Preview code, data, and lineage before anything ships. Works with dbt Core too — no platform account needed. [Sign up here](https://www.getdbt.com/wizard-desktop-waitlist) *** ## One agent. Available wherever data work happens. dbt Wizard works where you do. In the dbt platform or locally, it's grounded in your dbt project from the first prompt. ### dbt Wizard in platform (Preview) dbt Wizard gives your team a shared AI workspace inside the dbt platform, accessible from the browser with the controls admins need — no local setup required. Available in its own dedicated workspace and directly inside dbt Studio IDE. ### dbt Wizard Desktop (Private Beta) dbt Wizard Desktop, now available in private beta, is a desktop app that provides a dedicated local workspace to handle longer, more complex local work — multiple sessions running side by side, threads kept organized, with richer visualizations for the agent's multi-step builds. ### dbt Wizard CLI (Public Beta) A terminal-native agent for analytics engineers developing locally, whether you're a dbt platform customer or self-hosted. Everything Wizard knows about your project travels with you to the CLI — so you get accurate, context-aware help wherever you actually build. ![Image](https://cdn.sanity.io/images/wl0ndo6t/main/075516323ae45f223931b632d1b68ee65e62538d-1910x1080.gif) *** ## Ship your best dbt work without leaving your workflow Refactor, build, investigate, migrate and ship. All grounded in your dbt project, all in one place. *** *More features* ## Every part of the job, without breaking flow From migration to analysis to upgrades, dbt Wizard handles the work that slows teams down. ### Move models without breaking dependencies Describe what you're migrating and Wizard handles every ref, test, and YAML config — with a reviewable diff before anything saves. ### Get answers grounded in your dbt data Ask in plain language, get answers rooted in your defined metrics — traceable back to the models your team already trusts. ### Fix Fusion conformance errors, automatically Wizard reads your project, applies high-confidence fixes, and flags what needs your input. Get to Fusion faster with less manual effort. *** > > > — Farin Fukunaga, Paylocity > > > — Erion Krasniqi, Endress+Hauser InfoServ > > > — Vishal Kaviraj > > > — Michael Fridolfsson, Brighte *** ## Learn more ### Everything we announced at Snowflake Summit 2026 ### Watch our dbt Wizard on-demand webinar to see it action ### Read the docs and start building with dbt Wizard --- --- title: "Capabilities - Deploy" description: "Streamline CI/CD workflows, schedule jobs, and monitor deployments to ensure reliable, fresh data in production." url: "https://www.getdbt.com/product/deploy" --- # Simplify your data pipeline deployments. dbt provides the easiest, most reliable way to automate your pipelines from development to production. [Deploy your first project](https://www.getdbt.com/signup) | [Talk to an expert](https://www.getdbt.com/contact) *** *The Analytics Development Lifecycle* ## Seamless deployments for reliable data pipelines. The deploy phase of the Analytics Development Lifecycle (ADLC) ensures high-quality data reaches production consistently, automatically, and reliably. With dbt, you can schedule jobs, trigger runs on merges, or integrate with external tools to keep your data pipeline running smoothly. Learn how automated deployments, performance insights, and orchestrated exposures help teams optimize workflows and keep data fresh. [Read the ADLC whitepaper](https://www.getdbt.com/resources/the-analytics-development-lifecycle) *** *Deploy with dbt* ## Automate and orchestrate your pipelines to support decision-making. Stay in control whether you're managing complex data models or coordinating multiple teams. Easily schedule and orchestrate workflows across different environments to ensure smooth transitions from development to production. ### Reliable, timely data Keep production data consistently fresh and accurate, ensuring that your BI tools and end users always have the latest insights for informed decisions ### Increased visibility and control Gain insights into deployment health, identify issues quickly, and proactively optimize your data models and pipelines for better reliability and performance ### Efficient collaboration and CI/CD Ensure your continuous integration (CI) and continuous deployment (CD) workflows run smoothly, promoting tested code from development to production *** ## Powerful features power reliable deployments. dbt offers comprehensive deployment capabilities to automate, manage, and scale your data pipelines. ### Deliver quality code and data to production on schedule Ensure data freshness in even the most complex workflows. Visualize and orchestrate downstream exposures to understand how models are used in downstream tools and proactively refresh the underlying data sources during scheduled dbt jobs ![Deliver quality code and data to production on schedule](https://cdn.sanity.io/images/wl0ndo6t/main/7f671d7ef56fd54fc53ffdda58c494a02b24d7da-1224x1224.png) ### Embrace advanced scheduling capabilities and triggers Schedule jobs on your terms—whether on a fixed timeline or triggered by events—and use features like "defer to production" to test development workflows efficiently and safely. You can also trigger a job from an external pipeline or orchestrator through the dbt API ![Embrace advanced scheduling capabilities and triggers](https://cdn.sanity.io/images/wl0ndo6t/main/0d2d257857639f1b58b681294b1e68b6bebdb00f-1224x1224.png) ### Deploy to multiple isolated environments Manage and deploy data workflows across separate development and staging environments to test and validate changes before promoting your data production ![Deploy to multiple isolated environments](https://cdn.sanity.io/images/wl0ndo6t/main/fa8e3ec4db74d86c9c20730c1618496c01e6eb25-1224x1224.png) ### Monitor jobs with comprehensive alerts Get notifications via email and Slack to stay updated on deployments. Gain real-time visibility into model statuses, job performance, and deployment history to swiftly troubleshoot and optimize ![Monitor jobs with comprehensive alerts](https://cdn.sanity.io/images/wl0ndo6t/main/e18323d0b41d32d05b1e9c98d0a28b22930e04b7-1224x1224.png) ### Effortless CI/CD implementation Automate code testing in staging environments and ensure latest changes are reliably pushed to production upon merge ![Effortless CI/CD implementation](https://cdn.sanity.io/images/wl0ndo6t/main/4c54274c538d5ac25ab04ea26c392ec6acde2795-1224x1224.png) ### Hybrid project management Combine artifacts from dbt and dbt Core for centralized visibility, cross-project referencing, and streamlined collaboration, ensuring consistency and transparency across your deployments ![Hybrid project management](https://cdn.sanity.io/images/wl0ndo6t/main/88a31329a097b109097dbe4dc0232edca7c1af44-1224x1224.png) *** ## Deploy your data pipelines with dbt. dbt is how modern data teams ship and scale trusted data—from first model to federated data mesh [Book a demo](https://www.getdbt.com/contact) | [Explore dbt](https://www.getdbt.com/product/dbt) *** ## Proven by the best in data. Leading organizations rely on dbt to improve data quality and velocity. ### Siemens implements a data mesh architecture at scale with dbt Cloud > “Already in our first dbt Cloud project we were amazed by the seamless collaboration dbt Cloud offers, allowing us to effortlessly work together on the same Snowflake project. With built-in tests, simple job scheduling, and easy deployment, dbt Cloud enabled us to immediately focus on the business case rather than spending time on our data architecture setup.” [Read more](https://www.getdbt.com/case-studies/siemens) ### Rebtel improves data quality and data team productivity by migrating from Matillion to dbt Cloud > “Before, we couldn’t kick off any machine learning projects because incidents would happen. We had little visibility on our data lineage and code on Matillion, so we never really knew if the data was correct or complete. Now we’re working on an ML fraud prevention use case which will have a direct impact on our profit margins.” [Read more](https://www.getdbt.com/case-studies/rebtel) ### Fortune 500 oil & gas company embraces self-service analytics with agile data management > "I remember reading the dbt viewpoint and thinking this is fantastic — a simple way to focus on SQL as a way to manage data objects and at the same time solve our scheduling and dependency problems. dbt was an off-the-shelf solution that took our ideas to the next level. It was revelatory." [Read more](https://www.getdbt.com/case-studies/oil-and-gas) *** *Additional resources* ## Deploy your pipelines with confidence ### Defer to production Learn more about how you can save time and computational resources with the defer command. ### Visualize and orchestrate downstream exposures Automatically generate exposures from dashboards and proactively refresh the underlying data sources (like Tableau extracts) during scheduled dbt jobs. ### Job chaining Automate your dbt DAG while optimizing compute spend. *** ## Start deploying with dbt. Automate and scale your data pipelines effortlessly with dbt—from development to production. [Book your demo](https://www.getdbt.com/contact) | [Explore dbt](https://www.getdbt.com/product/dbt) --- --- title: "Capabilities - Develop" description: "Build, test, and deploy analytics workflows using dbt’s collaborative development tools, including Studio IDE, Canvas, and Copilot." url: "https://www.getdbt.com/product/develop" --- # Build with speed and confidence. Empower any data user to build reliable and governed data pipelines. [Start developing](https://www.getdbt.com/signup) | [Talk to an expert](https://www.getdbt.com/contact) *** *The Analytics Development Lifecycle* ## Develop faster with dbt. The develop phase of the Analytics Development Lifecycle (ADLC) is where ideas become actionable analytics. Whether you prefer the command line or a low-code experience, dbt meets you where you work. Learn how dbt’s web-based Studio IDE, drag-and-drop Canvas, VS Code extension, and AI-powered Copilot help teams build, test, and deploy analytics workflows at scale. [Read the ADLC whitepaper](https://www.getdbt.com/resources/the-analytics-development-lifecycle) *** *Develop with dbt* ## One platform. Multiple ways to develop. No matter your team’s level of SQL or coding experience, dbt offers various development environments to meet your teams where they are. The dbt VS Code Extension allows your most technical team members to work with familiar tooling. The dbt Studio IDE equips SQL-savvy developers for success in a browser-based UI. And the drag and drop interface in Canvas allows anyone with SQL familiarity to embrace analytics engineering best practices. ### Seamless collaboration across teams dbt enables teams to collaborate effectively, regardless of their technical proficiency. The platform's diverse development interfaces ensure that analysts and engineers can work well together, fostering a culture of shared ownership and continuous improvement. ### Accelerate onboarding and skill development dbt's intuitive interfaces, built-in best practices, and integrated learning resources help new users ramp up quickly. Whether they're analysts learning to build models or engineers expanding their impact, dbt shrinks the learning curve and enables every contributor to grow their analytics engineering skills. ### Security and governance dbt admins can ensure proper governance with built-in contracts, versions, and access controls. Enjoy all the bells-and-whistles you've come to expect from your enterprise software solutions—RBAC, SSO, audit logging, and more—right out-of-the-box. *** ## Features made to build reliable data pipelines. dbt offers a suite of features designed to streamline development, enhance collaboration, and ensure data quality across your organization. ### dbt Canvas brings any data user into the fold Empower anyone with SQL familiarity to author dbt models through a drag-and-drop interface with the new visual editing experience. Transformation logic still compiles directly to SQL and is backed by built-in testing, documentation, and version control ![dbt Canvas brings any data user into the fold](https://cdn.sanity.io/images/wl0ndo6t/main/7b97447386283f484aff68a5206c398cdcf29b5a-1224x1224.png) ### dbt Studio IDE Provide your team with a full-fledged development experience in their browsers, meaning no setup and no fuss. The dbt Studio IDE enables your team to start in minutes with built-in Git controls, code linting, lineage, and many more capabilities ![dbt Studio IDE](https://cdn.sanity.io/images/wl0ndo6t/main/438bdda4dd8b81893c96cb43ce52e20ab814bd44-1364x1364.png) ### The dbt VS Code extension encourages power users to reach their full potential Allow more technical team members to continue working with familiar tooling with the dbt VS Code extension. Integrate with popular software and boost productivity with a local development experience backed by all the features and performance of dbt ![The dbt VS Code extension encourages power users to reach their full potential](https://cdn.sanity.io/images/wl0ndo6t/main/5d07d767b5977e19a00fa6a458e4fe8f8c378403-1224x1224.png) ### dbt Copilot accelerates development with AI Build high quality data products faster with dbt Copilot, a context-aware AI assistant. ![dbt Copilot accelerates development with AI](https://cdn.sanity.io/images/wl0ndo6t/main/9f693ca2334d1736c014790c155872d06232c116-1224x1224.png) ### Maintain code quality and consistency wherever you build Linting helps enforce best practices and catch common errors early, while automatic SQL formatting keeps code readable and standardized—so teams can maintain clean, consistent code while focusing on logic, not style ![Maintain code quality and consistency wherever you build](https://cdn.sanity.io/images/wl0ndo6t/main/f74a9fbf61b6d20501232a39b16a0d7a65028b55-1224x1224.png) *** ## Build better with dbt. dbt is how modern data teams ship and scale trusted data—from first model to federated data mesh. [Book a demo](https://www.getdbt.com/contact) | [Explore dbt](https://www.getdbt.com/product/dbt) *** ## Proven by the best in data. Join leading companies transforming data into insights. ### Sunrun enables last mile modeling with dbt Cloud > “With data teams spanning several business functions, we didn't just need a way to standardize development. We needed a way for those processes to be easily understood by everyone—seasoned engineers, new analysts, the CFO... everyone.” [Read more](https://www.getdbt.com/case-studies/sunrun) ### Code42 increased data team productivity by switching from dbt Core to dbt Cloud > “Before dbt Cloud, we were happy if we could restore something the same day it broke. Now, we can preview results before merging, and my team no longer needs to switch between Snowflake and VS Code. The time saving there alone is just amazing.” [Read more](https://www.getdbt.com/case-studies/code42) *** *Additional resources* ## Learn how to develop faster with dbt. ### Intro to dbt Studio IDE dbt Studio IDE compiles dbt code into SQL and executes it directly on your database. [Read intro](https://docs.getdbt.com/docs/cloud/dbt-cloud-ide/develop-in-the-cloud) ### Get started with dbt Canvas Learn how dbt Canvas can help you quickly access and transform data through a visual, drag-and-drop experience. ### Get started with the dbt VS Code Extension *** ## Start developing with dbt. Ship trusted data models faster with powerful development interfaces in dbt. [Book your demo](https://www.getdbt.com/contact) | [Explore dbt](https://www.getdbt.com/product/dbt) --- --- title: "Solutions - Embedded Analytics" description: "Embed real-time, governed metrics into apps using dbt’s semantic layer to deliver trusted, scalable analytics to every user." url: "https://www.getdbt.com/product/embedded-analytics-use-cases" --- # Deliver data experiences customers love. Bring reliable, personalized analytics to any end-user experience, creating moments that truly wow. [Request your demo](https://www.getdbt.com/contact) | [Try dbt for embedded analytics](https://www.getdbt.com/signup) *** ## Make sure your metrics match. Inconsistent metrics in embedded dashboards erode trust. The dbt Semantic Layer ensures your data tells a single story—no matter where it shows up. - Trust your data - Ditch rigid dashboards - Build faster *** *Why dbt* ## Centralize metrics and delight your customers. Deliver governed, trustworthy metrics in your customer experiences with remarkable speed. Calculate complex metrics centrally with the dbt Semantic Layer, version-control them, and deliver them as customized, embedded visualizations wherever your customers consume data. ### Stand up analytics experiences faster With a powerful data model, caching layer, and access controls, delivering personalized metrics is as simple as configuring an API call ### Instill trust with quality data Centralize your metric logic with the dbt Semantic Layer to ensure your customer analytics are powered by the most secure, high-quality data ### Empower your customers with personalized insights The dbt Semantic Layer centralized complex metrics so data teams can confidently build relevant, personalized experiences with developer-friendly APIs and SDKs ### Scale without breaking the bank Cut operational costs and reduce server load by centralizing your business logic and metrics, simplifying maintenance, and improving system efficiency *** ### The dbt Semantic Layer Enable teams to define metrics once and embed them anywhere with confidence that calculations and logic remain consistent, while also simplifying governance, version control, and maintenance of metrics that appear in multiple embedded contexts ![The dbt Semantic Layer](https://cdn.sanity.io/images/wl0ndo6t/main/a3ac9f45927cd0fe321096adb3f5963d02366190-1224x1224.png) ### Data lineage UI Offer visibility into the entire data pipeline that powers embedded visualizations. Allow developers to quickly troubleshoot issues when embedded analytics break, validate data quality for customer-facing metrics, ensure regulatory compliance by documenting data flows, and facilitate smoother updates to embedded analytics as data models evolve ![Data lineage UI](https://cdn.sanity.io/images/wl0ndo6t/main/a3df3837c17bfe3b91d2bd1b2d5e403318259883-1224x1224.png) ### dbt governance controls Use dbt to manage who can modify customer-facing metrics, track lineage of embedded analytics, and enforce testing requirements before metrics reach production. Create a secure, reliable foundation for embedded analytics while maintaining regulatory compliance and data quality standards ![dbt governance controls](https://cdn.sanity.io/images/wl0ndo6t/main/c0b67c8c949649e6ec342f307d3ec96ff8e1a58f-1224x1224.png) *** ## Real-life Success Stories Explore how dbt Labs has helped to achieve better clients outcomes, increase efficiency, and grow their business. ### Bilt Rewards saves 80% in analytics costs with the dbt Semantic Layer > “By centralizing our entity relationships in the dbt Semantic Layer, where all of our data transformations already live, we could easily create visualizations in our B2B product. We delivered an improved data experience for our B2B partners by eliminating a step in our process, decreasing our data costs by 80%, and increasing reliability and trust.” [Read more](https://www.getdbt.com/case-studies/bilt-rewards) ### Secret Escapes modernizes web analytics with dbt Cloud > “With dbt Cloud, you can give analysts autonomy, while maintaining data governance. Our analysts have taken to it like ducks to water." [Read more](https://www.getdbt.com/case-studies/secret-escapes) *** *The dbt Community* ## Join the largest community shaping data & embedded analytics. The dbt Community is your gateway to best practices, innovation, and direct collaboration with thousands of data leaders and AI practitioners worldwide. Ask questions, share insights, and build better with the experts. [Join the Community](https://www.getdbt.com/community/join-the-community) | [Explore the Community](https://www.getdbt.com/community) *** *Why teams trust dbt* ## Trusted globally. Proven at scale. ### 80,000+ teams using dbt dbt powers trusted analytics workflows and data at scale for the world's largest companies ### 97% customer satisfaction Rated 4.9/5 on G2 by thousands of data leaders who trust dbt for critical analytics and AI initiatives. ### Built with leading partners ### 100K+ Community members Join the largest open data community sharing best practices and building better data products *** *Learn more* ## Dig deeper into embedded analytics with dbt ### Five use cases for the dbt Semantic Layer From AI to BI to embedded apps, learn how to deliver trusted data to any endpoint. ### Semantic Layer: What it is and when to adopt it Learn how the dbt Semantic Layer ensures your employees can easily find, trust, and use data even with a huge influx of data sources ### How Bilt Rewards delivered personalized analytics See how Bilt Rewards uses dbt’s Semantic Layer to embed personalized insights and enable a more efficient, trusted analytics environment *** *Get started* ## Start building with dbt. Streamline your data transformation process, reduce manual errors, and increase productivity with dbt. Sign up today an take your data transformation workflow to the next level [Request your demo](https://www.getdbt.com/contact) | [Build your analytics layer](https://www.getdbt.com/signup) --- --- title: "Product - Governance" description: "Implement access controls, versioning, and lineage tracking to ensure data quality and compliance with dbt." url: "https://www.getdbt.com/product/governance" --- # Drive governance with dbt Simplify complex systems and produce faster with the new playbook for data management. [Govern your data with dbt](https://www.getdbt.com/signup) | [Talk to an expert](https://www.getdbt.com/contact) *** ## Focus on strategy, not maintenance Invest in dbt to centralize governance and safely distribute access — for a more collaborative, trusted, and effective team. ### Workflow governance Allow data analysts and engineers to standardize on the same platform, with a single source of truth for metrics. ### Role & access governance Control who can ship changes and make sure that only high-quality transformations make it to production. ### Data governance Limit errors and make auditing a breeze with auto-generated docs, version control, integrated testing, and visual lineage. *** ## Accelerate speed to insight End siloed processes where analysts make the case for new data, and engineers add the request to a weeks-long backlog. You can’t scale analytics that way. dbt is a trusted platform that makes building data systems collaborative and agile, instead of a disjointed hand-off. [Book your demo](https://www.getdbt.com/contact) | [Explore dbt](https://www.getdbt.com/product/dbt) *** ## Advance data democracy Protect data models and pipelines with built-in guardrails — like audit logs, job fail notifications, and fine-grained access control. dbt provides these features out-of-the-box, so engineers can focus on high-value work, and analysts can self-serve insights quickly and safely. [Book a demo](https://www.getdbt.com/contact) | [Protect data pipelines with dbt](https://www.getdbt.com/signup) *** ## Optimize your platform Make the most your cloud data platform by using software development best practices — like version control, testing, CI/CD, and auto-documentation — for data transformations. dbt adds more efficiency, governance, and standardization to your data team’s work. [Optimize your data stack with dbt](https://www.getdbt.com/signup) *** ## Build trust with business Add transparency to your data development process with a visual DAG and templated IDE. Embedded governance makes it easy to understand the lineage of data transformations and add in a DataOps process for higher data quality, accurate results, and reliable reporting. [Build data transparency with dbt](https://www.getdbt.com/signup) *** ## Trusted by the best in data. Leading organizations rely on dbt to build modular, governed, high-performing data ecosystems. ### Pepperstone creates data decision makers can rely on > “Trust is so important because we are the experts in data analysis. And if you have a good level of trust, your insights are more likely to be robustly discussed.” [Read more](https://www.getdbt.com/case-studies/pepperstone) ### Siemens implements a data mesh architecture at scale with dbt Cloud > “Already in our first dbt Cloud project we were amazed by the seamless collaboration dbt Cloud offers, allowing us to effortlessly work together on the same Snowflake project. With built-in tests, simple job scheduling, and easy deployment, dbt Cloud enabled us to immediately focus on the business case rather than spending time on our data architecture setup.” [Read more](https://www.getdbt.com/case-studies/siemens) ### Retool builds scalable, self-serve analytics with dbt Cloud and Databricks > “dbt on Databricks allowed Retool to get value out of data really quickly. We were generating large quantities of product usage data and we needed insights without having to hire a data team first.” [Read more](https://www.getdbt.com/case-studies/retool) ### WHOOP improves efficiency by implementing dbt Core and migrating to dbt Cloud > “Access to accurate data is critical, it allows us to improve the customer experience and increase retention, lifetime value, and profitability.” [Read more](https://www.getdbt.com/case-studies/whoop) ### ### ### *** ## Start building with dbt Streamline your data transformation process, reduce manual errors, and increase productivity with dbt. Sign up today and take your data transformation workflow to the next level. [Talk to a governance expert](https://www.getdbt.com/contact) | [Start governing your data](https://www.getdbt.com/contact) --- --- title: "Product - Integrations" description: "Connect dbt with leading tools for data movement, BI, and governance to streamline your analytics workflows." url: "https://www.getdbt.com/product/integrations" --- # Explore dbt integrations Extend the analytics engineering workflow beyond dbt with seamless integrations covering a range of use cases across the Modern Data Stack. Discover integrations by product category below. [Integrate your stack](https://www.getdbt.com/signup) | [Talk to an integration expert](https://www.getdbt.com/contact) *** ## Cloud data platforms ### AlloyDB Connect to and run queries against underlying data in AlloyDB. [Learn more](https://docs.getdbt.com/docs/platform/connect-data-platform/connect-postgresql-alloydb?version=2) ### Amazon Redshift Connect to and run queries against underlying data in Redshift. [Learn more](https://docs.getdbt.com/guides/getting-started/getting-set-up/setting-up-redshift) ### BigQuery Connect to and run queries against underlying data in BigQuery. [Learn more](https://docs.getdbt.com/guides/getting-started/getting-set-up/setting-up-bigquery) ### Clickhouse Connect to and run queries against underlying data in Clickhouse. [Learn more](https://docs.getdbt.com/docs/platform/connect-data-platform/connect-clickhouse) ### Databricks Connect to and run queries against underlying data in a Databricks lakehouse. [Learn more](https://docs.getdbt.com/guides/getting-started/getting-set-up/setting-up-databricks) ### Microsoft Fabric Connect to and run queries against underlying data in Microsoft Fabric. [Learn more](https://docs.getdbt.com/docs/cloud/connect-data-platform/connect-microsoft-fabric) ### Snowflake Connect to and run queries against underlying data in Snowflake Data Cloud. [Learn more](https://docs.getdbt.com/guides/getting-started/getting-set-up/setting-up-snowflake) ### Starburst Run queries against distributed data sources using Starburst or Trino. [Learn more](https://docs.getdbt.com/docs/quickstarts/dbt-cloud/starburst-galaxy) ### Onehouse Connect to and run queries against underlying data in your Onehouse data lakehouse. [Learn more](https://docs.getdbt.com/docs/cloud/connect-data-platform/connect-onehouse) *** ## Data movement ### Airbyte Coordinate dbt jobs for data ingested from Airbyte’s connector catalog and your custom sources. [Learn more](https://docs.airbyte.com/cloud/managing-airbyte-cloud/dbt-cloud-integration) ### Fivetran Automatically and securely move your data and kick off downstream dbt jobs. [Learn more](https://fivetran.com/docs/transformations/dbt-cloud) ### Matia Move data efficiently and trigger downstream dbt jobs. [Learn more](https://www.matia.io/blog/all-about-matias-dbt-integration) ### Weld Easily move your data with Weld and trigger dbt jobs for automated workflows. [Learn more](https://weld.app/docs/dbt-cloud) *** ## Business intelligence and analysis ### Dot Enable everyone to analyze data with AI in Slack or Teams using dbt Semantic Layer. [Learn more](https://docs.getdot.ai/dot/integrations/dbt-semantic-layer) ### Google Sheets Query the dbt Semantic Layer and build reliable, governed reports within Google Sheets. [Learn more](https://docs.getdbt.com/docs/use-dbt-semantic-layer/gsheets) ### Hex Easily access and explore dbt metrics with the Metrics cell. Populate the schema browser inside Hex with dbt metadata. [Learn more](https://learn.hex.tech/docs/connect-to-data/data-connections/dbt-integration) ### Klipfolio Catalog and analyze dbt metrics -- confident decision-making for business teams. [Learn more](https://support.klipfolio.com/hc/en-us/articles/18164546900759-PowerMetrics-Adding-dbt-Semantic-Layer-metrics) ### Lightdash Build and share charts based on dbt metrics in just a couple of clicks. [Learn more](https://docs.lightdash.com/references/dbt-semantic-layer) ### Mode Explore dbt metrics in a drag-and-drop interface. Understand data freshness by pulling timestamp and origin information directly into reports. [Learn more](https://mode.com/help/articles/dbt-data-freshness/) ### Preset Define metrics and models in dbt and easily sync them to Preset to quickly explore your data and build interactive dashboards. [Learn more](https://docs.preset.io/docs/dbt-integration) ### Sigma Quickly import and access dbt metadata including descriptions, last refresh time, and test results inside Sigma. [Learn more](https://help.sigmacomputing.com/docs/manage-dbt-integration) ### Tableau Query the dbt Semantic Layer and build reliable, governed dashboards within Tableau. [Learn more](https://docs.getdbt.com/docs/use-dbt-semantic-layer/tableau) ### ThoughtSpot Instantly start searching and building Liveboards against data models and metrics created in dbt. [Learn more](https://docs.thoughtspot.com/cloud/latest/dbt-integration) *** ## Operational analytics and reverse ETL ### Census Connect your dbt models and materialize them directly into downstream sales and marketing tools. [Learn more](https://docs.getcensus.com/basics/triggering-syncs#dbt-cloud-integration) ### Hightouch Easily sync modeled data to downstream tools through a simple UI. Schedule syncs to run after select dbt jobs. [Learn more](https://hightouch.com/docs/syncs/dbt-cloud/) *** ## Data quality ### Anomalo Monitor data that feeds dbt metrics to ensure data quality issues are flagged and root-caused immediately. [Learn more](https://anomalo.com/post/automated-data-quality-monitoring-of-business-metrics-with-dbt-anomalo) ### Bigeye Find and fix data pipeline issues faster with ML-based anomaly detection and root cause analysis. [Learn more](https://docs.bigeye.com/docs/connect-dbt-cloud) ### Databand Visualize and monitor dbt jobs, models, and tests together with dependent upstream and downstream processes. [Learn more](https://www.ibm.com/docs/en/dobd?topic=integrations-dbt) ### Datafold See how dbt pull requests effect tables, columns, rows, and dashboards before merging to production. [Learn more](https://docs.datafold.com/integrations/orchestrators/dbt_cloud) ### Metaplane View metadata about dbt job runs such as run durations, models generated by dbt, and lineage relationships between models. [Learn more](https://docs.metaplane.dev/docs/dbt) ### Monte Carlo Easily troubleshoot incidents by surfacing associated dbt model and test run results inside Monte Carlo. [Learn more](https://docs.getmontecarlo.com/Docs/dbt-cloud) ### Soda Manage incidents from dbt test results that are stored over time in Soda Cloud Metrics Store. [Learn more](https://docs.soda.io/soda/integrate-dbt.html) ### Synq Enhance your dbt tests with anomaly monitors dynamically deployed with rules based on your metadata. [Learn more](https://docs.synq.io/dbt-integrations/dbt-cloud) *** ## Data catalogs ### Acryl Data View models, docs, test results, and column-level lineage across your dbt projects and downstream dashboards. [Learn more](https://datahubproject.io/docs/generated/ingestion/sources/dbt/#module-dbt-cloud) ### Alation Access end-to-end lineage, model descriptions, and curated context to accelerate data migration and build more reliable data pipelines. [Learn more](https://www.alation.com/partners/dbt-labs/) ### Atlan Pull in metadata and metrics from your dbt project, enjoying end-to-end column-level lineage. Explore metrics using Atlan’s Visual Query Builder. [Learn more](https://ask.atlan.com/hc/en-us/sections/6319211562897-dbt-Connectivity) ### Collibra Allow more people across your organisation to find, understand, trust and access the right data at the right time with Collibra and dbt metrics. [Learn more](https://marketplace.collibra.com/listings/dbt-cloud/) ### Euno View, enhance and optimize dbt models and metadata using Euno's automated data discovery and dbt code-generation. [Learn more](https://docs.euno.ai/sources/dbt-cloud) ### Secoda Enhance your dbt models, metrics, and documentation in Secoda with automatic column and dashboard lineage. [Learn more](https://docs.secoda.co/integrations/data-transformation-tools/readme-1) ### Select Star Import metadata and docs from your dbt project. Gain visibility on column-level lineage for dbt models. [Learn more](https://docs.selectstar.com/integrations/dbt/dbt-cloud) *** ## Orchestration ### Airflow Use Airflow or Astronomer to orchestrate and execute dbt models as DAGs. [Learn more](https://registry.astronomer.io/providers/dbt%20Cloud/versions/latest) ### Dagster Dagster allows you to run dbt Cloud jobs alongside other technologies. You can schedule them to run on a regular basis, and as part of larger pipelines. [Learn more](https://docs.dagster.io/integrations/dbt-cloud) ### Prefect Schedule and run dbt jobs from within Prefect. [Learn more](https://docs.prefect.io/integrations/prefect-dbt) *** ## Data Monitoring ### Datadog Monitor the performance of dbt job runs and visualize model execution time with Datadog. [Learn more](https://docs.datadoghq.com/integrations/dbt_cloud/) *** *Why teams trust dbt* ## Trusted Globally. Proven at scale. ### 80,000+ teams using dbt. dbt powers trusted analytics workflow and data at scale for the worlds largest companies ### Top-rated on G2 Recognized in Gartner’s DataOps Market Guide 2024. ### Built with leading partners ### 100K+ Community members Join the largest open data community sharing the best practices and building better data products. *** *Learn more* ## Get under the hood with dbt. Unpack what makes dbt so powerful for so many teams—from product fundamentals to strategy shifts and architectural deep dives. ### Read the State of Analytics Engineering Report ### dbt: The control plane for data collaboration at scale ### Fast track to dbt *** *Get started* ## Build trust, move faster, an cut costs. Discover how dbt works as your team’s control plane for trusted, scalable data. [Book a demo](https://www.getdbt.com/contact) | [Start integrating your data stack](https://www.getdbt.com/signup) --- --- title: "Self-hosting dbt vs. dbt platform" description: "Stop maintaining infrastructure. dbt platform gives your team managed transformations, governed collaboration, and built-in AI — without the overhead." url: "https://www.getdbt.com/product/self-hosting-dbt-vs-dbt-platform" --- # Your team didn't get into data ||to maintain pipelines Many nimble data teams start with self-hosting dbt. dbt platform gives you the governance, computer efficiency, ||and AI readiness that self-hosted dbt can't. Let's get you ready for the AI future. [Book a demo](https://www.getdbt.com/contact) | [Start free trial](https://www.getdbt.com/signup) *** *Why dbt platform* ## What dbt platform delivers for customers: Move from maintenance to impact. Cut compute costs, eliminate tooling sprawl, and give every team and AI tool a data foundation you trust. Reduction in dbt-related compute spend Fewer data quality incidents hours per week of time reclaimed by engineering teams *** ## Where are you in the dbt journey? *** ## Trusted by 5,700+ organizations including: - Hubspot - jetBlue - New Relic - Nasdaq - BHP - Domain *** ## Self-hosting dbt vs dbt platform A closer look at what’s included with self-hosting dbt vs. dbt platform. *** *Get started* ## Ready to build on dbt, not around it? Talk to someone who's helped teams like yours make the shift. 30 minutes. No pitch deck. Just your questions. [Book a demo](https://www.getdbt.com/contact) | [Start a free trial](https://www.getdbt.com/signup) --- --- title: "Capabilities - Analyze" description: "Define metrics once and deliver consistent, governed insights across tools with dbt’s Semantic Layer, powered by MetricFlow." url: "https://www.getdbt.com/product/semantic-layer" --- # From exploration to AI, trusted analysis starts with dbt. Move faster, trust your data, and scale self-service—all with a unified layer for metrics and governance. [Explore the semantic layer](https://www.getdbt.com/signup) | [Book a demo](https://www.getdbt.com/contact) *** *The Analytics Development Lifecycle* ## Define metrics once. Use them everywhere. The analyze phase of the ADLC is where business decisions take shape—but inconsistent metrics, slow queries, and scattered tools can quickly erode trust. With dbt's Semantic Layer and AI-powered dbt Insights, teams get fast, intuitive access to governed models and standardized metrics so they can explore data with confidence. Learn how semantic models, lineage visualization, and query optimization help teams stay aligned and move faster. [Read the ADLC whitepaper](https://www.getdbt.com/resources/the-analytics-development-lifecycle) *** *Analyze with dbt* ## Reliable metrics mean less guessing about data. Work with consistently defined metrics and get the same answers—everywhere, every time. The dbt Semantic Layer centrally defines what key terms mean so you know exactly what data you're delivering. ### Define once. Trust everywhere. Define your metrics and logic from a single governed source, so your team works with the same secure definitions across every report, embedded app, and AI workflow—every time. ### Improve access to reliable data Give non-technical business users access to self-serve metrics and logic, whether in dashboards, agents, or directly in dbt, to make timely decisions with accurate information. ### Serve insights with lightning speed Give your team a speed boost with performance- and query-optimized access to consistent, governed metrics defined in dbt *** ## Build fast, scalable AI and analysis on a trusted foundation. Deliver consistent insights and AI at scale by centralizing metric definitions and governing access—all from a single source of truth. ### Set and standardize your metrics Define governed semantic models and metrics as code using easy-to-configure YAML files. Everything is version-controlled, lineage-aware, and built for transparency—so you can trust that metrics like revenue or orders are consistent across every dashboard, app, and agent. ![Set and standardize your metrics](https://cdn.sanity.io/images/wl0ndo6t/main/5e6ccb3846e07382de34777c4b1781356cbebf5b-1039x897.png) ### Consistent metrics, everywhere you need them Metrics aren't just for BI. With a robust API, the dbt MCP Server, and dozens of out-of-the-box integrations, the dbt Semantic Layer lets you push governed, consistent definitions to embedded analytics, notebooks, spreadsheets, AI systems, and more—so every decision and experience is built on trusted data ![Consistent metrics, everywhere you need them](https://cdn.sanity.io/images/wl0ndo6t/main/b68738d55916507cf61daf05ba0001947fd90db9-1224x1224.png) ### Faster queries, lower costs Query at scale and control costs with MetricFlow, the query engine behind the dbt Semantic Layer. It automatically rewrites queries to minimize compute and latency, uses pattern matching to optimize joins, and leverages caching to reduce redundant queries, so teams get faster answers at a lower cost, even across complex joins and metrics ![Faster queries, lower costs](https://cdn.sanity.io/images/wl0ndo6t/main/a14fa82b2a5e2d31542593611d01152badf25f28-1224x1224.png) ### Turn questions into insights, instantly With dbt Insights, you have an AI-powered analysis tool that lets you ask questions and get answered from governed data faster. Using simple code or natural language prompts you can create queries, validate models, generate visualization, and easily share findings, all within dbt. ![Turn questions into insights, instantly](https://cdn.sanity.io/images/wl0ndo6t/main/bcc7ffaba2bb5a0551520f5b136ba5bd601c93c0-1224x1224.png) *** ## Power your analytics with governed, AI-ready data. From dashboards to copilots—dbt is how modern teams serve trusted insights fast. [Book a demo](https://www.getdbt.com/contact) | [Explore dbt](https://www.getdbt.com/product/dbt) *** ## Proven by the best in data and AI. See how top organizations use dbt to power modern self-serve analytics and AI with confidence. ### Bilt Rewards saves 80% in analytics costs with the dbt Semantic Layer > “By centralizing our entity relationships in the dbt Semantic Layer, where all of our data transformations already live, we could easily create visualizations in our B2B product. We delivered an improved data experience for our B2B partners by eliminating a step in our process, decreasing our data costs by 80%, and increasing reliability and trust.” [Read more](https://www.getdbt.com/case-studies/bilt-rewards) ### Code42 increased data team productivity by switching from dbt Core to dbt Cloud > “Before dbt Cloud, we were happy if we could restore something the same day it broke. Now, we can preview results before merging, and my team no longer needs to switch between Snowflake and VS Code. The time saving there alone is just amazing.” [Read more](https://www.getdbt.com/case-studies/code42) ### Inventa Builds Confidence in Data Through the dbt Semantic Layer > “One thing I used to hear a lot was 'can I trust this data?' Now everyone knows: if it's there in the warehouse, you can trust it because it's been tested and centralized.” [Read more](https://www.getdbt.com/case-studies/inventa) *** *Additional resources* ## Dig into the dbt Semantic Layer. Learn more about how the dbt Semantic Layer can help you deliver trusted data anywhere. ### Why your AI will fail without a semantic layer The semantic layer enforces guardrails, ensuring the AI system queries only approved, governed, and contextualized metrics. ### Five use cases for the dbt Semantic Layer From AI to BI to embedded apps, learn how to deliver trusted data to any endpoint. ### Streamline dashboards with the dbt Semantic Layer Learn how dbt Labs consolidated metrics for faster, trusted data delivery. *** ## Start deploying with dbt. Automate and scale your data pipelines effortlessly with dbt—from development to production. [Book your demo](https://www.getdbt.com/contact) | [Explore dbt](https://www.getdbt.com/product/dbt) --- --- title: "Use Cases - dbt Semantic Layer" description: "Discover how dbt’s Semantic Layer enables consistent metrics across BI, AI, embedded analytics, and self-serve tools." url: "https://www.getdbt.com/product/semantic-layer-use-cases" --- # Consistent metrics for business results. Learn the different ways you can make impact automatic with the dbt Semantic Layer, or get more specifics in our blog post on use cases. [Request your demo](https://www.getdbt.com/contact) | [Explore more in the blog](https://www.getdbt.com/blog/five-use-cases-for-the-dbt-semantic-layer) *** *Who uses dbt* ## Write it once, use it anywhere, and trust the results with dbt Semantic Layer Centralize your metric logic alongside your data models and deliver governed, consistent insights to any BI tool, API, or large language model (LLM). ### For business stakeholders Never second-guess KPI dashboards. Enable self-serve via AI chatbots and no-code interfaces ### For data scientists Train your ML models and conduct exploratory analytics using governed metrics ### For customers Embed personalized and meaningful metrics across user experiences *** ### Reporting & BI Report the right numbers to the board, every time. Build your KPI scorecards from centrally-defined metrics and trust that the data is accurate. Easily explore contextual data like lineage, definitions, and joins so you can always be 100% confident in the metrics you share. [Read more on how we used dbt Semantic Layer to meet users where they are, with trusted data.](https://www.getdbt.com/blog/streamlining-kpi-dashboards-dbt-semantic-layer) ![Image](https://cdn.sanity.io/images/wl0ndo6t/main/bd2e81757c4637380c193f99993f7a064d267914-3600x2400.webp) ### Embedded analytics Include meaningful metrics in your customer experiences. Calculate complex metrics with the dbt Semantic Layer and deliver them as up-to-date, embedded visualizations in your app. [Read how Inventa uses the dbt Semantic Layer to build trust and confidence in their data.](https://www.getdbt.com/case-studies/inventa) ![Image](https://cdn.sanity.io/images/wl0ndo6t/main/a6d57ff25f2f84e7981ce4f4fdfec1c2f2fe3faa-3600x2400.webp) ### AI & LLM Query data without a PhD in data engineering. Ask a question like, “What was revenue in Germany last month?” to your preferred LLM and get the right answer lightning fast. Better yet: ask any permutation of that question (by product, channel, or anything you want) without any additional engineering work—[all powered by the centralized, standard metrics in your warehouse.](https://www.getdbt.com/product/ai) ![Image](https://cdn.sanity.io/images/wl0ndo6t/main/2c0dedbcd8c5e2b386b10713634a8220bcfbb90a-3600x2400.webp) ### Self-serve analytics Allow non-technical users to tap into your metrics. They’ll be empowered to confidently answer their own questions based on the governed semantic building blocks you’ve created. They get the insights they need, and you can ensure the quality and governance posture of that data without ever fielding an ad hoc request. It’s a win/win. [See all our integrations.](https://docs.getdbt.com/docs/cloud-integrations/avail-sl-integrations) ![Image](https://cdn.sanity.io/images/wl0ndo6t/main/6d3c04198e2ca139fc34dde9326ebf1ec6d6eb75-3600x2400.webp) ### Exploratory analytics Supercharge your data teams with a governed sandbox to explore metrics and unearth new insights. Join data defined in the semantic layer—[or anywhere in your warehouse](https://docs.getdbt.com/docs/dbt-cloud-apis/sl-api-overview)—and sync metrics into your preferred notebook as you collaborate on your next big idea. ![Image](https://cdn.sanity.io/images/wl0ndo6t/main/7047a5ce1a8c57e130c76a9ed7debade941f0fdd-3600x2400.webp) *** > > > — Gabriel Marinho, Inventa > > > — Hans Nelsen, Brightside *** ## Join the largest community shaping data & AI. The dbt Community is your gateway to best practices, innovation, and direct collaboration with thousands of data leaders and AI practitioners worldwide. Ask questions, share insights, and build better with the experts. [Join the Community](https://www.getdbt.com/community/join-the-community) | [Explore community resources](https://www.getdbt.com/community) *** *Learn more* ## Dig deeper into the dbt Semantic Layer ### Five use cases for the dbt Semantic Layer From AI to BI to embedded apps, learn how to deliver trusted data to any endpoint. ### Join the dbt Semantic Layer workshop Join us for a two-hour course designed to give you a clear understanding of the dbt Semantic Layer. ### Got a question? We’ve got answers. Dive deep into the dbt Semantic Layer FAQs and get your questions answered right away. *** *Why teams trust dbt* ## Trusted globally. Proven at scale. ### 80,000+ teams using dbt dbt powers trusted analytics workflows and data at scale for the world's largest companies ### 97% customer satisfaction Rated 4.9/5 on G2 by thousands of data leaders who trust dbt for critical analytics and AI initiatives. ### Built with leading partners ### 100K+ Community members Join the largest open data community sharing best practices and building better data products *** *Get started* ## Start building with dbt. Streamline your data transformation process, reduce manual errors, and increase productivity with dbt. Sign up today an take your data transformation workflow to the next level [Request your demo](https://www.getdbt.com/contact) | [Create a free account](https://www.getdbt.com/signup) --- --- title: "Capabilities - Test & Observe" description: "Automate tests, monitor pipelines, and resolve issues quickly with dbt’s integrated data quality tools." url: "https://www.getdbt.com/product/test-and-observe" --- # Make high-quality data automatic. Proactively test and continuously integrate your code so you know it's ready for prime time, then stay ahead of data issues with continuous monitoring and observability. [Start testing free](https://www.getdbt.com/signup) | [Talk to an expert](https://www.getdbt.com/contact) *** *The Analytics Development Lifecycle* ## Find & fix data issues—fast. Broken data pipelines are a nightmare. With testing and observability in key phases of the Analytics Development Lifecycle, you can proactively catch issues before they hit production—and quickly resolve the ones that do. Learn how automated tests, SQL validation, and built-in observability help teams maintain data quality and reliability at scale. [Read the ADLC whitepaper](https://www.getdbt.com/resources/the-analytics-development-lifecycle) *** *Why dbt* ## Ensuring data quality is simple for everyone. dbt offers proactive ways to test and integrate hardened code, and ingrains building high-quality data pipelines in the development workflow. ### Build proactive tests Ensure data integrity with automated, customizable tests that keep your models accurate and reliable. ### Validate code before merging into production Embrace CI to test code and catch breaking changes or unexpected behavior before new data is delivered to your stakeholders ### Spot, troubleshoot, and resolve issues fast Leverage detailed lineage, logs, and real-time alerts to swiftly address issues, maintaining trust in your data *** ## Test and observe in dbt. Leverage built in features designed to proactively ensure and maintain data quality across your pipeline. ### Proactive testing every step of the way Build confidence into your development workflow with unit, integration, and data tests. Proactively define assertions for how you expect your models to behave or validate the logic within your model—before ever materializing that model in production ![Proactive testing every step of the way](https://cdn.sanity.io/images/wl0ndo6t/main/d1eb31cb90e6a8d821d0eab1b13fd6590bd7ca41-1224x1224.png) ### Continuous integration Embrace CI to test code and catch breaking changes or unexpected behavior before new data is delivered to your stakeholders ![Continuous integration](https://cdn.sanity.io/images/wl0ndo6t/main/0e2d27e782cc18c1ee1508d6eabf127b33c9faa7-1224x1224.png) ### Monitoring & alerts Spot, troubleshoot, and resolve issues fast. Observe run history to identify long-running or broken models. Use column-level lineage and audit logs to pinpoint root cause fast. Real-time alerts mean you can keep pipelines humming without worrying stakeholders ![Monitoring & alerts](https://cdn.sanity.io/images/wl0ndo6t/main/04e227ae77bce395ff3a95ade74dcf92c8b68308-1224x1224.png) *** ## Build better with dbt today. dbt is how modern data teams ship and scale trusted data—from first model to federated data mesh. [Book a demo](https://www.getdbt.com/contact) | [Explore dbt](https://www.getdbt.com/product/dbt) *** ## Proven by the best in data. Learn how teams are using dbt to deliver quality data across their organization. ### Rocket Money modernizes financial reporting with dbt Cloud > "Having this automated Quote-to-Cash system run in dbt with our test suite allows us to confidently and quickly close our books each month." [Read more](https://www.getdbt.com/case-studies/rocket-money) ### Watercare builds a scalable, resilient data warehouse with dbt Cloud > “All of the improvements driven by dbt Cloud are starting to add up, and the quality of our data has exponentially grown. We can put testing in place and enforce rules to ensure that data going to users is correct without having to spend time manually checking it.” [Read more](https://www.getdbt.com/case-studies/watercare) ### Tempo builds a virtual personal trainer with dbt Cloud and Stemma > “Growing from five to 300 people meant we needed more consistent data, version control, testing, discoverability—all the features that we could get with dbt Cloud and Stemma” [Read more](https://www.getdbt.com/case-studies/tempo) *** *Additional resources* ## Learn more about data quality in dbt ### Test smarter, not harder Unlock the full potential of your tests by focusing on what matters most—data you can trust. ### Unit Testing in dbt See how the new unit testing framework brings precision and speed to testing logic in dbt models. ### Add data tests to your DAG Learn how to validate your data with built-in and custom tests that catch issues before they impact downstream dashboards. [Read FAQs](https://docs.getdbt.com/docs/build/data-tests) *** ## Validate your inputs and verify your outputs with dbt. Empower your teams to have more confidence in every commit with proactive testing and streamlined observability. [Book your demo](https://www.getdbt.com/contact) | [Explore dbt](https://www.getdbt.com/product/dbt) --- --- title: "What is dbt" description: "Transform raw data into reliable insights with dbt’s modular, cloud-native platform built for collaboration and scale." url: "https://www.getdbt.com/product/what-is-dbt" --- # The standard for data transformation. dbt turns data work into a shared, scalable practice by bringing software engineering to the analytics workflow. Powered by an engine built in Rust, dbt is built for speed, scale, and how teams and agents work today. [Install dbt](https://docs.getdbt.com/docs/local/install-dbt?install-method=pip&version=2) | [Explore dbt platform](https://www.getdbt.com/product/dbt) *** *What makes dbt different* ## Turn raw data into reliable data products. Create trusted data products that power analytics, operations, and AI. ### Trusted by design dbt brings modularity, testing, and version control to your transformations. It catches errors before warehouse execution and automatically generates rich metadata your agents can trust. ### Open and flexible dbt is grounded in open standards, runs on every major data platform, and works with the tools you already use—on your machine or in dbt platform. ### Fast and cost-optimized at scale dbt compiles projects in seconds and rebuilds only what’s changed, reducing developer wait time and compute costs. *** ## Engineering rigor for analytics teams. ### Define transformations in code Write modular models as SQL SELECT statements that reflect your business logic, then reference them anywhere. Change the logic once and everything downstream inherits it. ![Diagram showing a dbt model definition using a ref function to query the stg_jaffle_shop_customers model, transforming customer data for use in product_analytics.](https://cdn.sanity.io/images/wl0ndo6t/main/71926d421915cec51ed893e8bf1eedf27d2e4b06-1224x1224.png) ### Validate as you type dbt delivers real-time intelligence directly in your editor. Catch errors, validate columns, and see full lineage as you build before anything hits the warehouse. ![Diagram showing how you can validate columns and catch errors as you type, before anything hits the warehouse](https://cdn.sanity.io/images/wl0ndo6t/main/c27fcaeb2a400982c31780e3343951c0a08c68c0-1340x1224.webp) ### Test as you build Write and run tests to catch anomalies early, so bad data never reaches a dashboard or agent. ![Image showing a dbt test configuration for the customer_id column in the stg_jaffle_shop_customers model, validating uniqueness and non-null constraints using the dbt test command.](https://cdn.sanity.io/images/wl0ndo6t/main/2ec07ec67cc0939aa8debde07c831022b9bef2ee-1224x1224.png) ### Document and share context Add descriptions, tags, and ownership to models and columns, all searchable through automatically generated docs and backed by column-level lineage. ![Screenshot of a dbt model detail view for dim_customers_v3, showing description, unique ID link, project name, and exposure type metadata within dbt Cloud.](https://cdn.sanity.io/images/wl0ndo6t/main/dc1054cdda25b4d72769370e0a95c9813e3e3d88-1224x1224.png) ### Version-control your logic Use Git to version every change, with code review, change tracking, and project-wide refactoring when logic needs to move. ![GitHub pull request view in dbt Cloud, showing model-level changes with indicators for modified, added, and removed rows, plus a 4% row difference warning before merging.](https://cdn.sanity.io/images/wl0ndo6t/main/3654ae10d306cb4ea06dcd9c3b29017ed9ea9124-1224x1224.png) *** *Built-in efficiency* ## Rebuild only what’s changed With every run, dbt State checks your warehouse for changes in model SQL or data. It builds only what changed, and automatically skips the rest by reusing, cloning or auto-deferring. This allows you to simplify orchestration, iterate faster in governed dev environments, and save on warehouse compute. Teams like Obie have seen up to **30% savings on compute** and reclaimed engineering hours. [Read their story](https://www.getdbt.com/blog/how-obie-cut-compute-costs-by-30-percent) | [Learn more](https://www.getdbt.com/product/dbt-state) *** *Built for agents* ## Context your AI agents can trust dbt automatically generates structured, queryable metadata as you build: column-level lineage, types, and dependencies, formalized as the dbt information schema. Your AI agents work from your real project instead of guessing from stale docs, so the code they write matches your actual schema. [Learn more](https://www.getdbt.com/product/ai) *** ## See dbt at work. ### Siemens implements a data mesh architecture at scale with dbt Cloud > “Already in our first dbt Cloud project we were amazed by the seamless collaboration dbt Cloud offers, allowing us to effortlessly work together on the same Snowflake project. With built-in tests, simple job scheduling, and easy deployment, dbt Cloud enabled us to immediately focus on the business case rather than spending time on our data architecture setup.” [Read more](https://www.getdbt.com/case-studies/siemens) ### Obie Insurance > We're saving at least 30% on compute costs, just from reusing models with dbt State [Read more](https://www.getdbt.com/case-studies/obie-insurance) ### AXS delivers business value with an analytics engineering workflow > “dbt Cloud is great because it’s so approachable. You can log in on your browser, select a project, and start building models right away. You can build things with native SQL that you’d think were only possible with Python or a more object-oriented language. The SQL-first approach creates commonality among the tech teams, improving communication and collaboration.” [Read more](https://www.getdbt.com/case-studies/axs) ### How RMIT University evolved its data platform without a disruptive redesign using the dbt Fusion engine > “With the dbt Fusion engine, the performance improvements showed up across the entire development experience. Teams spent less time waiting for processes to complete, moved changes through the pipeline faster, and could focus more of their time on building and delivering data products.” [Read more](https://www.getdbt.com/case-studies/rmit-university) *** ## Trusted by top-tier data teams. - Affirm - Nasdaq - Canva - Duolingo - TaskRabbit - GitLab *** *Learn more* ## See what dbt can do for your business. Unpack what makes dbt powerful—from product fundamentals to strategy shifts and architectural deep dives. ### Get started with dbt Quickstarts ### How analysts at JetBlue improved data trust and delivery by 95% ### WHOOP improves efficiency with dbt *** ## across the data stack - BigQuery - Databricks - Fabric - Fivetran - Redshift - Snowflake *** *Join 100,000+ data professionals* ## Great data work never happens alone. The dbt Community connects you with thousands of data practitioners, leaders, and learners—all solving real problems, sharing best practices, and growing their careers together. - - - [Join the Community](https://www.getdbt.com/community/join-the-community) | [Explore Community resources](https://www.getdbt.com/community) --- --- title: "Report a Problem" description: "Encounter an issue? Report it to help us enhance dbt Labs' website and ensure a better experience for all users." url: "https://www.getdbt.com/report-a-problem" --- # Report a problem with our website Experiencing a problem on our website? Fill out the form and we'll take a look. Please make sure to include as much detail as possible in your submission. We will contact you once the problem has been addressed. --- --- title: "SDF" description: "Bringing the most advanced SQL understanding to your favorite data tool." url: "https://www.getdbt.com/sdf" --- # dbt Labs acquires SDF Labs dbt Labs acquires SDF Labs to introduce robust SQL comprehension into dbt and supercharge developer efficiency. [Read press release](https://www.getdbt.com/blog/dbt-labs-announces-sdf-labs-acquisition) | [Explore dbt Cloud](https://www.getdbt.com/product/dbt-cloud) *** ## Learn more about our acquisition of SDF ### dbt Labs acquires SDF Labs to accelerate the dbt developer experience The two teams are already working side-by-side to bring SDF’s SQL comprehension technology into the hands of dbt users everywhere. [Read more](https://www.getdbt.com/blog/dbt-labs-acquires-sdf-labs) ### Advancing the vision for the data control plane with SDF and dbt Since launching into GA in mid-2024, SDF has quickly emerged as a powerful tool in the data analytics space. [Read more](https://www.getdbt.com/blog/advancing-the-data-control-plane-vision-with-sdf-and-dbt) ### Accelerating dbt with SDF Watch dbt Labs founder Tristan Handy and SDF Labs co-founder, Lukas Schulte, as they talk about the significance of bringing these two great technologies together. [Watch on-demand](https://www.getdbt.com/resources/webinars/accelerating-dbt-with-sdf) *** ## More from our developer experience team ### The Three Levels of SQL Comprehension: What they are and why you need to know about them Ever since dbt Labs acquired SDF Labs last week, I've been head-down diving into their technology and making sense of it all. The main thing I knew going in was "SDF understands SQL". It's a nice pithy quote, but the specifics are fascinating. [Read more](https://docs.getdbt.com/blog/the-levels-of-sql-comprehension) ### The key technologies behind SQL Comprehension In this post, we’ll talk about the technologies that underpin SQL Comprehension tools in more detail. Hopefully, you come away with a deeper understanding of and appreciation for the hard work that your computer does to turn your SQL queries into actionable business insights! [Read more](https://docs.getdbt.com/blog/sql-comprehension-technologies) ### Building the next-gen dbt engine: How SDF levels up data tooling With the integration of SDF under the hood, dbt will be both much faster and significantly more cost-efficient — while unlocking new metadata use-cases like true column-level lineage. In the first post, we covered SQL comprehension — why it matters, and how it can be done at three distinct levels of precision. [Read more](https://www.getdbt.com/blog/building-the-next-gen-dbt-engine) *** ## Want to learn more? Check out these resources to find out how dbt Cloud can help your teams ship trusted data faster. ### ADLC Whitepaper Learn about how to scale workflows across the analytics development lifecycle. [Read the whitepaper](https://www.getdbt.com/resources/guides/the-analytics-development-lifecycle) ### 2025 State of Analytics Engineering Report This year's report highlights a sector that is evolving at breakneck speed. [Read the report](https://www.getdbt.com/resources/reports/state-of-analytics-engineering-2025) ### Manage data complexity at scale eBook Learn how to balance agility with quality, even in complex environments. [Read the eBook](https://www.getdbt.com/resources/manage-data-complexity-at-scale-ebook) *** *Join 100,000+ data professionals* ## Great data work never happens alone. The dbt Community connects you with thousands of data practitioners, leaders, and learners—all solving real problems, sharing best practices, and growing their careers together. - - - [Join the Community](https://www.getdbt.com/community/join-the-community) | [Explore Community resources](https://www.getdbt.com/community) --- --- title: "Security" description: "Explore how dbt safeguards your data with top-tier security measures and compliance certifications, ensuring trust and reliability." url: "https://www.getdbt.com/security" --- # Ship securely without compromise Your data security matters, which is why we’ve designed our systems, applications, and processes to safeguard your data as if it were our own. dbt has been engineered at every level to handle your most sensitive data. [Build on a secure foundation](https://www.getdbt.com/signup) | [Talk to an expert](https://www.getdbt.com/contact) *** ## Deliver data quality with high security Maintain your data security posture with the strongest encryption standards. dbt maintains an A+ rating from Qualys/SSL and requires communications to use the strongest encryption protocols so you can ship high-quality data with low risk. We have continuous monitoring and development to identify possible issues and keep our systems up to date. *** ## Run your code fast on our secure infrastructure Keep your data protected on a platform that’s proven safe and secure. Our processes are continually tested and maintained to the highest standards, and we partner with top experts to stay up to date with the latest security techniques. This includes third party providers that continuously challenge our systems with rigorous penetration testing to find weak points before they can be exploited. *** ## Compliance - **** - **** - **** - **** - **** - **** - **** - **** - **** *** ## Security Highlights The entire dbt team is focused on keeping you and your data safe. We use industry standards including OWASP, NIST, ISO 27001, ISO 27701, and ISO 42001 to guide our security program and engineering practices. ### Access management dbt Labs has implemented a number of access controls to ensure the confidentiality, integrity and availability of dbt. All access is provisioned by role and the principle of least privilege. Our controls include multi-factor authentication requirements, strong passwords, an identity provider, Zero Network Trust Access tooling for production environments, mobile device management and quarterly access reviews to name a few. ### Asset management - dbt Labs has established configuration standards across all of its managed endpoints to ensure assets are configured securely and identically. - Laptops are protected by full disk encryption using FileVault2, and managed by an industry-leading MDM. - A tool is in place to enforce the use of standard production images for production servers_._ ### Availability, business continuity, & disaster recovery - dbt is _primarily_ hosted in AWS, and deployed across multiple AZ’s (availability zones) in a region. - Our retention of backups are a minimum of seven (7) days. - Our staff is remotely distributed across the world providing support to customers globally. Our distributed workforce allows us to provide support virtually from anywhere and reduce the impact of support interruption in a geographic location. - Our Business Continuity, Disaster Recovery, and Incident Response Plans are tested annually to ensure effectiveness and organizational readiness. ### Communication encryption - All connections to dbt are encrypted by default, in both directions using modern ciphers and cryptographic systems. We maintain an A+ rating from [Qualys/SSL Labs](https://www.ssllabs.com/ssltest/analyze.html?d=cloud.getdbt.com&s=54.175.47.110). We support both TLS 1.2 and TLS 1.3 to encrypt data in transit. - Any attempt to connect over HTTP is redirected to HTTPS. - We use HSTS to ensure browsers interact with dbt only over HTTPS - We utilize AES-256 for all data encrypted at rest. - For additional information about dbt Architecture, please visit [https://docs.getdbt.com/docs/cloud/about-cloud/architecture](https://docs.getdbt.com/docs/cloud/about-cloud/architecture) ### Data processing Data remains in your data warehouse – we don’t upload or download it. Your query is created on the frontend of our tool in your browser (it is not cached by dbt Labs), behind your firewalls and VPN, and is not accessed by any of our employees unless you screen share with our support team. Even if you use a preview pane, that is also under your control or that of the data warehouse and is not accessible from our systems. Once written or as scheduled, the query runs through the IDE’s backend. dbt Labs has set up the backend to be fully automated and is not accessible by dbt Labs personnel unless a problem occurs to the tool, and then only the personnel capable of diagnosing and fixing a problem would have access. For development purposes, analysts can write queries from the IDE against development data, for example: “select * from customers limit 100,” the data from your development customers table will pass through the dbt infrastructure on the way to your browser. Data does not live on our servers outside of your ephemeral session. _dbt Labs employees are not able to access those sessions._ Upon request for Enterprise accounts, this IDE Preview functionality can be disabled. ### Data storage dbt stores the following data persistently: 1. dbt account information including job definitions, database connection information, users, etc. dbt account information does not include any raw data from your warehouse. 2. Logs associated with jobs and interactive queries you’ve run. 3. Your dbt “assets” which include things like run_results.json and manifest.json. Generally, logs and other dbt assets do not contain client data stored in its data storage location unless your user directs such storage. For example, it’s theoretically possible to write a command that instructs the data warehouse to write your data into a dbt log. Please note that we strongly advise against transferring client stored data to our logs. There is no reason for such an action. Unless otherwise indicated, dbt is [hosted](https://docs.getdbt.com/docs/cloud/about-cloud/architecture) in multiple regions and will connect to your data platform or git provider from the IP addresses found [here](https://docs.getdbt.com/docs/cloud/about-cloud/regions-ip-addresses#fnref-1). Be sure to allow traffic from these IPs in your firewall, and include them in any database grants. [dbt Enterprise](https://www.getdbt.com/pricing/) plans can choose to have their account hosted in any of the regions found [here](https://docs.getdbt.com/docs/cloud/about-cloud/regions-ip-addresses#fnref-1). Organizations **must** choose a single region per dbt account. If you need to run dbt in multiple regions, we recommend using multiple dbt accounts. For more information, please visit this [link](https://docs.getdbt.com/docs/cloud/about-cloud/regions-ip-addresses#fnref-1). ### Penetration testing dbt undergoes annual penetration testing by an independent third-party provider, and regularly updates all underlying software to the latest secure versions. ### Research and disclosure dbt Labs is committed to working with security researchers across the world to keep our systems secure. If you believe you have found a security vulnerability in dbt Core, dbt, or another dbt Labs product, we encourage you to let us know right away. We will investigate all legitimate reports and do our best to quickly fix the problem. Please review our Security Bug Bounty Program at [www.getdbt.com/security/disclosure](https://www.getdbt.com/security/disclosure). If you believe you have discovered a problem or have any questions, please contact us at [bug-bounty@dbtlabs.com](mailto:bug-bounty@dbtlabs.com). ### Security protocols - dbt’s data centers are hosted using Amazon Web Services, Microsoft Azure, or Google Cloud Platform at the client's discretion, where they are protected by electronic security, intrusion detection systems, and 24/7/365 human staff. - dbt uses actively maintained, long-term-supported operating systems that are kept up to date with the latest security patches. - dbt uses a dedicated firewall and private network to prevent unauthorized network access. - We limit access to sensitive data to those with a business reason for access. ### Shift left (SDLC) - dbt Labs follows a shift left security model to ensure security is engaged early and often throughout development. - Our engineers are required to complete secure code training at least annually and they follow OWASP guidelines per our Security Development Lifecycle. - All code must be peer reviewed before production, as part of our Change Management Policy. - A security and privacy data protection impact assessment must be completed for all product feature requests and product feature changes. ### Vulnerability scanning New vulnerabilities or new patches are detected from the various monitoring and scanning dbt Labs has in place. Vulnerabilities are addressed based on severity through various processes, at which time the vulnerability is closed out. Critical vulnerabilities are addressed within 7 days, and High-severity vulnerabilities are addressed within 30 days. Engineering tracks all vulnerabilities through resolution. *** *Get started* ## Start building with dbt. Streamline your data transformation process, reduce manual errors, and increase productivity with dbt. Sign up today an take your data transformation workflow to the next level. [Request your demo](https://www.getdbt.com/contact) | [Start building today](https://www.getdbt.com/signup) --- --- title: "Security Disclosure" description: "Learn how to report security vulnerabilities to dbt Labs. Review our bug bounty scope, guidelines, and responsible disclosure process." url: "https://www.getdbt.com/security/disclosure" --- # Security Bug Bounty Program *** ## Overview dbt Labs wants to engage the security community to help improve security for our users and products. We sponsor our security bug bounty program through which we may provide rewards to security researchers who responsibly disclose valid security issues. All rewards will be provided at the discretion of dbt Labs and are subject to change without notice. dbt Labs runs a private bug bounty program through Bugcrowd and we would be happy to invite you, if you have an account. If you do not have a Bugcrowd account, please go through the registration process [here](https://bugcrowd.com/user/sign_up). ## Scope and Reporting All security testing will be conducted using black box testing methodology against our production environments. ✉️ Reports should be via Bugcrowd, once you have been invited to the private program. To request an invite to our Bugcrowd private program, please send an email to [bug-bounty@dbtlabs.com](mailto:bug-bounty@dbtlabs.com). We will respond as quickly as we can with an invitation. Please make sure the subject is clear that this is a bug bounty invitation request (e.g., Bug Bounty: Invitation Request). ### In Scope The following domains have been approved for testing: - *.dbt.com - *.dbtlabs.com - *.getdbt.com We operate in a multi-cloud environment so ensure that you adhere to [Amazon’s Penetration Testing Policy](https://aws.amazon.com/security/penetration-testing/), [Microsoft’s Penetration Testing Policy](https://www.microsoft.com/en-us/msrc/pentest-rules-of-engagement), and Google Cloud Platform’s [Acceptable Use Policy](https://cloud.google.com/terms/aup) and [Terms of Service](https://cloud.google.com/terms/). The underlying infrastructure, to include cloud hosting companies, is subject to change without notice. ### Explicitly Out of Scope - Denial of Service (DoS/DDoS) attacks. If you believe you may have a DoS-related vulnerability then email [bug-bounty@dbtlabs.com](mailto:bug-bounty@dbtlabs.com) and we can assess setting up a testing environment for the test. - Social engineering attacks. These include anything that would require another user to be coerced into navigating to or interacting with an attack. Examples include, but are not limited to: - Phishing - Website spoofing - Link manipulation (e.g., changing an “l” to a “1” in a url to deceive a user) - Brute force attacks (e.g., to access a user’s account). - Accessing another user’s data by any means. If you need to test an exploit that will interact with another user then set up a second user account for testing or reach out to [bug-bounty@dbtlabs.com](mailto:bug-bounty@dbtlabs.com) if you need specific testing requirements. - Testing against dbt Labs' physical properties, employees’ properties, or data centers. - [getdbt.com](http://getdbt.com) subdomains clearly operated by third-parties are explicitly out of scope, including, [discourse.getdbt.com](http://discourse.getdbt.com), [shop.getdbt.com](http://shop.getdbt.com), [trust.getdbt.com](http://trust.getdbt.com), [roundup.getdbt.com](http://roundup.getdbt.com), [assessment.getdbt.com](http://assessment.getdbt.com), and [credentials.getdbt.com](http://credentials.getdbt.com) ### Vulnerabilities Excluded from Rewards Depending on their impact, some of the reported issues may not qualify if they do not present a considerable amount of risk to the business. Below are some examples of non-qualifying security issues. - Disclosure of known public files or directories, (e.g., robots.txt). - Clickjacking and issues only exploitable through clickjacking. - CSRF on forms that are available to anonymous users (e.g., the contact form). - CSRF attacks that require knowledge of the CSRF token (e.g., attacks involving a local machine). - Logout cross-site request forgery (logout CSRF). - Content spoofing. - Login or Forgot Password page brute force and account lockout not enforced. - OPTIONS HTTP method enabled. - Username/email enumeration. - Missing HTTP security headers, specifically ([https://www.owasp.org/index.php/List_of_useful_HTTP_headers](https://www.owasp.org/index.php/List_of_useful_HTTP_headers)), such as: - Strict-Transport-Security. - X-Frame-Options. - X-XSS-Protection. - X-Content-Type-Options. - Content-Security-Policy, X-Content-Security-Policy, X-WebKit-CSP. - Content-Security-Policy-Report-Only. - Cache-Control and Pragma - HTTP/DNS cache poisoning. - SSL/TLS issues, such as: - SSL attacks such as BEAST, BREACH, Renegotiation attack. - SSL forward secrecy not enabled. - SSL weak/insecure cipher suites. - Self-XSS reports will not be accepted. - Similarly, any XSS where local access is required (i.e., User-Agent Header injection) will not be accepted. The only exception will be if you can show a working off-path MiTM attack that will allow for the XSS to trigger. - Subdomain takeover without proof of exploitability. - Missing or incorrect SPF records of any kind. - Missing or incorrect DMARC records of any kind. - Source code disclosure vulnerabilities. - Information disclosure of non-confidential information. - Email bombing/flooding/rate limiting. - Google Maps API Keys. - Vulnerabilities that require the user/victim to perform extremely unlikely actions (e.g., bypassing default security configurations in common web browsers). - Submission of user credentials obtained (e.g., public database dumps) ## Rewards All rewards will be provided at the discretion of dbt Labs via Bugcrowd and are subject to change without notice. ### Severities Our vulnerability rating system uses five severities: Critical, High, Medium, Low, and Informational. We evaluate submissions and assign severity based on our assessment of business risk. #### Critical Any vulnerability that would lead to full compromise of dbt Labs application, infrastructure, or data. Examples include: - Gaining privileged access to infrastructure - Gaining remote (e.g., shell) access to containers, infrastructure, or supporting applications - Gaining ability to export or delete databases #### High Any vulnerability that where the compromise of a sensitive data would lead to lateral movement. Examples include: - Ability to steal user access keys and using them to gain access to another application within dbt Labs. - Gaining access to portions of the infrastructure where man-in-the-middle operations could be conducted. #### Medium Any vulnerability that would lead to compromise of a sensitive data. Examples include: - Ability to steal user access keys - Ability to change data associated with other users - Persistent cross-site scripting (XSS) that can access another user’s settings #### Low Any vulnerability that would lead to performance degradation or data spillage. Examples include: - Application vulnerability via API endpoint manipulation - UI bug via data input that could cause performance or security issues - Subdomain takeover with proof that data is flowing to that subdomain #### Informational Issues that have no specific security impact. Examples include: - Lack of implemented security practices that may not apply in our specific context - Disclosure of information about the application environment - Debug statements ### Valid Submissions Valid submissions will receive a response within the order in which they were received. Once a submission has been assessed a severity by Bugcrowd and/or dbt Labs, if it is assessed Low or higher, then we will reward the bounty. ## **Legal Disclosure** We are unable to issue rewards to individuals who are on US sanctions lists, or who are in countries on US sanctions lists as indicated in our [terms of use](https://www.getdbt.com/terms-of-use). You are responsible for any tax implications depending on your country of residency and citizenship. There may be additional restrictions on your eligibility for the program depending upon your local law. This is not a competition, but rather an experimental and discretionary rewards program. You should understand that we can cancel the program at any time and the decision as to whether or not to reward is entirely at our discretion. dbt Labs rewards bug bounty hunters on a first-come, first-served basis, so if you report a vulnerability that is already known, it is not eligible for reward. There is no guarantee of a reward if a report is submitted. We will not share findings from other submitters. Your testing must not violate any law, disrupt our systems, or compromise any data that is not your own. If you have any questions, please contact [bug-bounty@dbtlabs.com](mailto:bug-bounty@dbtlabs.com). ## Definitions - **Black** **Box**. Type of testing where we share no sensitive information with the testers. We do not grant special access and the main goal is to test from the perspective of an attacker who has no internal knowledge of the systems. - **Business** **Impact**. A qualitative assessment of how a vulnerability will impact the business based on mitigating controls, quantitative assessments (e.g., CVSS), environmental factors, and other internal metrics that could be used to assess the impact of the vulnerability. --- --- title: "Services" description: "Partner with dbt Labs experts to design, implement, and scale your analytics workflows with confidence." url: "https://www.getdbt.com/services" --- # Modernize your data stack with expert guidance Implement the best tools and strategies for high-quality data development with help from dbt Labs Professional Services. [Get started](#get-started) *** ## Access mentorship and technical expertise Enlist an expert who'll guide your team through adopting—or optimizing—a modern data stack. Resident Architects or Analytics Engineers provide guidance, strategies, and custom solutions for your needs. ### Work with experts Build a trusted, modern data stack and solve your toughest use cases with assistance from experienced experts. ### Accelerate success Speed high-quality production and get the most from dbt by working directly with dbt Labs team members. ### Reduce costs Avoid expensive errors and wasted time with mentoring on dbt implementation, administration, and integration. *** ## Learn from an experienced Resident Architect Receive personalized guidance from a Resident Architect: a trusted technical advisor embedded into your organization with extensive expertise in dbt, cloud data warehouses, CI/CD, and the modern data stack. Your Resident Architect will assist with training, project design, and solution prototyping—and will connect your data warehouse, Git, and SSO provider if you're new to dbt. [Get started](#get-started) *** ## Get high-quality analytics engineering as a service Gain advanced technical assistance from an Analytics Engineer who can help with data modeling, project refactoring and design, and the migration of legacy transformations to dbt. They'll work closely with your team for a jointly defined scope, and at the end of your project, you'll receive your code and documentation. [Get started](#get-started) *** ## Ready to get started? Send us an email at services@dbtlabs.com to get in touch. --- --- title: "Sign up" description: "Create your dbt account to start building reliable, governed data pipelines. Experience streamlined analytics engineering from day one." url: "https://www.getdbt.com/signup" --- # Sign up for dbt dbt accounts are free forever for solo developers, or you can try it with your team for 14 days. Large or complex project? [Talk to a dbt expert](https://www.getdbt.com/contact/). - Quick to set-up - Easy to use - Try it with your team **You're in good company** *** *Why teams trust dbt* ## Trusted globally. Proven at scale. ### 80,000+ teams using dbt dbt powers trusted analytics workflows and data at scale for the world's largest companies ### Top-rated on G2 Recognized in Gartner's DataOps Market Guide 2024 ### Built with leading partners ### 100K+ Community members Join the largest open data community sharing best practices and building better data products --- --- title: "Legal - Software and Service Specific Requirements for Fivetran Products" url: "https://www.getdbt.com/software-and-service-specific-requirements-for-fivetran-products" --- ## Software and Service Specific Requirements for Fivetran Products _Effective _6/1/26 These Software and Service Specific Requirements for Fivetran Products (these "Requirements") apply to clients that have purchased or been granted access to Fivetran Products (as defined below) under an Order Form (“Client” or “Customer”). These Requirements supplement the terms of (a) the dbt Labs Terms of Service or other agreement for Client’s use of the dbt Labs Services (the "Terms") entered into between dbt Labs, LLC, as successor to dbt Labs, Inc. ("dbt Labs") and Client; and (b) the dbt Labs Data Processing Addendum or similar agreement for dbt Labs’ processing of Personal Data on behalf of Client in connection with Client’s use of dbt Labs Services and Fivetran Products (the "DPA", and together with the Terms, the "Agreement") entered into between dbt Labs and Client. Capitalized terms used but not defined herein will have the meanings given to them in the Agreement (or, if not defined in the Agreement, in the dbt Labs Terms of Service located at [https://www.getdbt.com/terms-of-service](https://www.getdbt.com/terms-of-service) or the dbt Labs Data Processing Addendum located at [https://www.getdbt.com/cloud/dpa](https://www.getdbt.com/cloud/dpa), or such successor URLs as may be designated by dbt Labs). ### 1. DEFINITIONS Notwithstanding anything to the contrary in the Agreement, for purposes of Client’s use of the Fivetran Products, the following definitions apply: - **"Customer Data" or “Data” **means any data that Client or its Authorized Users upload to or transmit through a Fivetran Product. - **"Documentation" **means Fivetran’s usage documentation for the applicable Fivetran Product made available on Fivetran’s website. - **"Fivetran" **means Fivetran Inc., a Delaware corporation. - **"Fivetran Product" **means (a) a SaaS-based data integration product ("SaaS Product"), (b) a downloadable data integration software component or product installed on premise or in Client’s private cloud environment ("On-Prem Software"), or (c) any combination or hybrid thereof, in each case provided by Fivetran. - **“Personal Data” **means the personal data described in Annex I as attached to these Requirements. - **“Software and Service Specific Requirements”** means the requirements for certain of the Fivetran Products and Professional Services located at https://www.fivetran.com/legal/service-specific-requirements, solely to the extent Client uses such Fivetran Products or Professional Services. - **"Source and Target Systems" **means with respect to On-Prem Software, the permitted type and number of computer hardware systems, storage platforms and computer frameworks from which Client may use such On-Prem Software, as identified in the applicable Order Form. - **“System Data”** means data, information or outputs derived by dbt Labs from the use of a Fivetran Product, including logs, statistics, or reports regarding the performance, availability, usage, integrity or security of the Fivetran Product (e.g., a user’s path through the Fivetran Product, login frequency, query logs, etc.). For the avoidance of doubt, System Data does not include Customer Data and does not relieve dbt Labs from otherwise complying with its confidentiality obligations under the Agreement with respect to Customer Data. - **“Third Party Platform”** means any product, add-on or platform not provided by dbt Labs that Client uses with the Fivetran Product. ### 2. PROVISION OF FIVETRAN PRODUCTS **2.1 Scope**. Except as modified herein, the Agreement governs Client’s use of the Fivetran Products and every reference to the Services therein will be deemed to also refer to the Fivetran Products so that the rights and obligations therein continue to apply. Fivetran, the parent company of dbt Labs, may provide the Fivetran Products, or a portion thereof, to Client in accordance with the Agreement, these Requirements and any applicable Order Form. dbt Labs will (a) be responsible for the portions of the Fivetran Products provided by Fivetran; and (b) not be relieved of its obligations under the Agreement, these Requirements or the applicable Order Form if Fivetran provides the Fivetran Products or a portion thereof. Notwithstanding anything in the Agreement or these Requirements to the contrary, Customer may execute one or more Order Forms directly with Fivetran for the Fivetran Products and (a) each such Order Form shall be governed by the terms and conditions of the Agreement, as modified and supplemented by these Requirements; and (b) dbt Labs shall be an express third party beneficiary of such Order Form, with the right to enforce the terms thereof as if dbt Labs were a party thereto. **2.2 On-Prem Software License.** With respect to any Order Form that includes On-Prem Software, subject to the terms of the Agreement and these Requirements, dbt Labs grants to Client a limited, non-exclusive, non-transferable (except as part of a permitted assignment of the Agreement under Section 13.2 (Assignment) of the Terms), non-sublicensable, royalty-free, worldwide license during the subscription term of such Order Form to install, integrate and use for its own internal business purposes such On-Prem Software on the Source and Target Systems. ### 3. PRIVACY AND SECURITY **3.1 Security.** Notwithstanding anything to the contrary in the Agreement, any security provisions and any security exhibits in the Agreement related to the dbt Labs Services will not apply to the Fivetran Products. Instead, dbt Labs will procure that Fivetran maintains administrative, physical, and technical safeguards for protection of the security, confidentiality and integrity of Customer Data submitted to the Fivetran Products in accordance with the Fivetran security policy located at [https://fivetran.com/docs/security](https://fivetran.com/docs/security) (the "Fivetran Security Policy") posted as of the Effective Date (as the Fivetran Security Policy may be updated by Fivetran in a manner that does not materially decrease the applicable protections for the Fivetran Products during the term of the applicable Order Form). **3.2 Privacy. **For purposes of these Requirements, notwithstanding anything to the contrary in the Agreement and solely with respect to the Processing of Personal Data in connection with the Fivetran Products, the DPA is modified as follows: (a) dbt Labs will process Personal Data for the following purposes: (i) as described in Schedule 1 of these Requirements, which hereby replaces Schedule 1 of the DPA (Details of the Processing and Transfer of Subscriber Personal Data); (ii) in accordance with the documented reasonable instructions of Client (which instructions, where Client is a processor, will reflect the instructions of its controller) that are consistent with the terms of the Agreement, these Requirements, applicable Order Forms, and Data Protection Laws; and (iii) to comply with dbt Labs’ legal obligations. (b) Schedule 2 of the DPA (Technical and Organisational Security Measures) is modified as set forth in Schedule 2 of these Requirements; (c) Schedule 3 of the DPA (Authorised Subprocessors) is modified as set forth in Schedule 3 of these Requirements. (d) “Security Incident” means any breach of security leading to the accidental or unlawful destruction, loss, alteration, or unauthorised disclosure or access to Personal Data that is in violation of dbt Labs’ security obligations under the Terms by dbt Labs or its agents of which dbt Labs becomes aware. Security Incident will not include an unsuccessful security incident, which is one that results in no unauthorized access to Personal Data or to any dbt Labs equipment or facilities storing the Personal Data, and could include (without limitation) pings and other broadcast attacks of firewalls or edge servers, port scans, unsuccessful log-on attempts, denial of service attacks, packet sniffing (or other unauthorized access to traffic data that does not result in access beyond headers) or similar incidents (e) Transfer Mechanisms. To the extent Client’s use of Fivetran Products requires an onward transfer mechanism to lawfully transfer personal data from a jurisdiction to dbt Labs located outside of that jurisdiction (“Transfer Mechanism”), the transfer of Personal Data will be subject to a single Transfer Mechanism, as applicable, and in accordance with the following order of precedence: (i) the EU-US Data Privacy Framework (“DPF”), the UK extension to the EU-US Data Privacy Framework, and the Swiss-US Data Privacy Framework self-certification program operated by the US Department of Commerce as applicable; (ii) Standard Contractual Clauses as set forth in the DPA; and, if neither (i) nor (ii) is applicable, then (iii) such other applicable Transfer Mechanisms permitted under Data Protection Laws. (f) dbt Labs shall ensure that any contract with its subprocessors including terms at least as protective as the ones contained in the Agreement. (g) Where required by the U.S. Health Insurance Portability and Accountability Act of 1996 ("HIPAA"), Client agrees not to upload to any SaaS Product any personal health information ("PHI Data") unless a Business Associate Agreement ("BAA") has been duly executed. Unless a BAA is in place, neither dbt Labs nor Fivetran will have liability under the Agreement for PHI Data, notwithstanding anything in the Agreement, or pursuant to HIPAA or any other applicable law. (h) Notwithstanding anything to the contrary in this Agreement, dbt Labs may collect System Data and use such data internally to develop, improve, support, and operate Fivetran Products. dbt Labs’ use of System Data will comply with Data Protection Laws. dbt Labs owns all right, title, and interest in System Data. dbt Labs may not share any System Data that includes Personal Data with a third party except to the extent the System Data is aggregated and anonymized such that Client and Client’s users cannot be identified. ### 4. SUPPORT POLICY AND SLA Notwithstanding anything to the contrary in the Agreement, technical support for the Fivetran Products will not be subject to dbt Labs’ support. Instead, technical support for the Fivetran Products are governed by the Fivetran Support Policy located at [https://www.fivetran.com/legal/support-policy](https://www.fivetran.com/legal/support-policy). In addition, use of the Fivetran Products is not subject to any service level agreement or SLA in the Agreement, and such use will instead be governed by the Fivetran SLA at [https://www.fivetran.com/legal/sla](https://www.fivetran.com/legal/sla). **5. SERVICE CONSUMPTION TABLE** Notwithstanding anything to the contrary in the Agreement or an Order Form, any provisions related to Fees, including as it related to Units, in the Agreement or an existing Order Form will not apply to the Fivetran Products. Instead, the Fivetran Service Consumption Table located at [https://www.fivetran.com/legal/service-consumption-table](https://www.fivetran.com/legal/service-consumption-table) (the "Service Consumption Table") will apply to the Fivetran Products unless otherwise set forth in the applicable Order Form. If Client’s use of a Fivetran Product exceeds the usage or capacity set forth on the applicable Order Form, or otherwise requires the payment of additional Fees (per the terms of the Agreement, these Requirements, or the Order Form), dbt Labs will invoice Client in arrears for such additional usage or capacity and Client agrees to pay the additional Fees in the manner provided herein. Billing communications will be addressed to ar@fivetran.com. ### 6. RESTRICTIONS AND REQUIREMENTS Client will use the Fivetran Products in accordance with the Fivetran Acceptable Use Policy located at [https://www.fivetran.com/legal/acceptable-use-policy](https://www.fivetran.com/legal/acceptable-use-policy) and the Software and Service Specific Requirements. ### 7. TRADE LAWS Client agrees to comply with, and shall not permit Authorized Users or any third parties to access or use the Fivetran Products in violation of international export controls and economic and trade sanctions laws and regulations (collectively, “Trade Laws”). Without limiting the foregoing, Client represents that it (a) will not access the Services from a country or territory that is itself the subject or target of trade or economic sanctions (a “Sanctioned Country”). ### 8. PRE-COMMERCIAL OFFERINGS Any Fivetran Product or feature offered on a trial basis will be deemed a "Beta Feature" for all purposes of Section 13.10 (Beta Features Terms) of the Terms. ### 9. LIMITATION OF LIABILITY AND INDEMNIFICATION NOTWITHSTANDING ANYTHING TO THE CONTRARY IN THE AGREEMENT, THE AGGREGATE, CUMULATIVE LIABILITY OF DBT LABS (INCLUDING ITS AFFILIATES AND THEIR DIRECTORS, OFFICERS, EMPLOYEES, REPRESENTATIVES, AGENTS AND SUPPLIERS) FOR OBLIGATIONS AND CLAIMS RELATED TO CUSTOMER DATA, WILL NOT EXCEED TWO TIMES (2X) THE AMOUNTS PAID OR PAYABLE BY CLIENT UNDER THE APPLICABLE ORDER FORM DURING THE TWELVE MONTH PERIOD PRIOR TO THE EVENT GIVING RISE TO THE CLAIM (“SPECIAL CAP”). NOTWITHSTANDING ANYTHING TO THE CONTRARY IN THE AGREEMENT, CLIENT WILL INDEMNIFY AND DEFEND DBT LABS AND ITS AFFILIATES AND THEIR RESPECTIVE OFFICERS, DIRECTORS AND EMPLOYEES (COLLECTIVELY, “DBT LABS INDEMNIFIED PARTIES”) FROM AND AGAINST ANY DAMAGES AND COSTS FINALLY AWARDED AGAINST THE DBT LABS INDEMNIFIED PARTIES OR AGREED TO IN SETTLEMENT BY CLIENT (INCLUDING REASONABLE ATTORNEYS’ FEES) IN CONNECTION WITH ANY CLAIMS ARISING FROM OR RELATED TO CUSTOMER DATA OR THEIR USE WITH THE FIVETRAN PRODUCTS, AS APPLICABLE, PROVIDED DBT LABS’ USE OF THE CUSTOMER DATA IS IN ACCORDANCE WITH THE AGREEMENT. SUCH INDEMNITY IS NOT SUBJECT TO THE LIMITATION OF LIABILITY SET FORTH IN THE AGREEMENT. ### 10. EFFECTIVE DATE AND UPDATES TO THESE REQUIREMENTS These Requirements take effect immediately upon Client’s use of the Fivetran Products. dbt Labs may update these Requirements from time to time. Any updates will become effective for Client upon renewal or entry into a new Order Form enabling the Fivetran Products after any updates go into effect. ### 11. MISCELLANEOUS Except as otherwise set forth in these Requirements, the terms of the Agreement, including, without limitation, any disclaimers, limitations of liability and governing law provisions set forth therein, will apply to Client’s use of the Fivetran Products. #### Schedule 1 to the DPA **Annex I to the DPA — Data Processing Description (applicable to Fivetran Products only)** This Annex I forms part of the DPA and describes the processing that the processor will perform on behalf of the controller. **A. LIST OF PARTIES** **Controller(s) / Data exporter(s):** _[Identity and contact details of the controller(s) / data exporter(s) and, where applicable, of its/their data protection officer and/or representative in the European Union]_ **Processor(s) / Data importer(s):** _[Identity and contact details of the processor(s) / data importer(s), including any contact person with responsibility for data protection]_ **B. DESCRIPTION OF TRANSFER** **C. COMPETENT SUPERVISORY AUTHORITY** #### Schedule 2 to the DPA **Annex II to the DPA — Technical and Organisational Security Measures (applicable to Fivetran Products only)** Description of the technical and organisational measures implemented by the processor(s) / data importer(s) (including any relevant certifications) to ensure an appropriate level of security, taking into account the nature, scope, context and purpose of the processing, and the risks for the rights and freedoms of natural persons. [Comparison table] **For transfers to (sub-) processors, the specific technical and organisational measures to be taken by the (sub-) processor:** **Contractual language** Fivetran ensures that its sub-processors are subject to substantially similar terms that provide equivalent data protection. **Due Diligence** Fivetran conducts due diligence on third parties, including necessary privacy and security reviews, such as privacy threshold and privacy impact assessments. Fivetran will: • Take reasonable steps and conduct due diligence to select and retain sub-processors capable of maintaining the privacy, confidentiality, security, integrity and availability of Personal Data consistent with Fivetran’s contractual and other legal obligations; • Contractually require sub-processors to maintain adequate safeguards for Personal Data sufficient to allow Fivetran to meet its contractual and legal requirements; and • Assess and monitor sub-processors to confirm their compliance with the applicable privacy and information security requirements. #### Schedule 3 to the DPA **Annex III to the DPA — List of Subprocessors (applicable to Fivetran Products only)** The current list of sub-processors authorised to process Personal Data in connection with the Fivetran Products is maintained at [https://fivetran.com/docs/security-and-privacy/privacy#subprocessormanagement](https://fivetran.com/docs/security-and-privacy/privacy#subprocessormanagement) (or such successor URL as may be designated by Fivetran). Fivetran provides notice for any additions to such list. Client may request a preferred email contact to receive notifications of changes by sending the contact to privacy@fivetran.com. Client agrees that Client’s configuration of access to a Fivetran Product (including selection of region or hosting environment) constitutes Client’s consent to Fivetran’s and dbt Labs’ use of the corresponding sub-processors for the Fivetran Products. This paragraph does not apply to changes made solely at the request of Fivetran or dbt Labs in the absence of Client’s instructions, direction or request. --- --- title: "Services Descriptions for Statements of Work" url: "https://www.getdbt.com/sow-services-descriptions" --- # Services Descriptions for Statements of Work *** Click the links below to open a PDF and read the service descriptions related to statements of work. **Current Services (To Be Deprecated)** - [dbt Cloud Onboarding: Bronze](https://www.getdbt.com/dbt-assets/dbt-cloud-onboarding-partner-bronze) - [dbt Cloud Onboarding: Silver](https://www.getdbt.com/dbt-assets/dbt-cloud-onboarding-partner-silver) **New Service Names (Launched May 1, 2026)** - [Resident Architect](https://www.getdbt.com/assets/docs/resident-architect.pdf) - [dbt Project Migration](https://www.getdbt.com/dbt-assets/dbt-project-migration) - [dbt Onboarding](https://www.getdbt.com/dbt-assets/dbt-onboarding) - [dbt Group Training](https://www.getdbt.com/dbt-assets/dbt-group-training) --- --- title: "Spreadsheets" description: "Bring governed, real-time metrics into Google Sheets and Excel using dbt’s Semantic Layer." url: "https://www.getdbt.com/spreadsheets" --- # Keep the spreadsheets, fix the chaos No more manual data prep or inconsistent metrics — with the dbt Semantic Layer, your spreadsheets become trusted, error-free tools. [Book a demo](https://www.getdbt.com/contact) | [Sign up for free](https://www.getdbt.com/signup) *** ## Data teams around the world love dbt - Affirm - Nasdaq - Canva - Duolingo - TaskRabbit - GitLab - Hubspot - jetBlue - Air New Zealand - Thermo Fisher Scientific - Conde Nast - Vestas - Altis Consulting - Domain - New Relic - Anheuser-Busch Group - Hotelbeds - CHG Healthcare - Talkdesk - Virgin Media *** ## From simple to complex. Trusted metrics in any sheet. Say goodbye to static tables. MDX queries and OLAP cubes. With real-time SQL dynamically generated at query time, the dbt Semantic Layer brings up-to-date, centralized data to Google Sheets and Excel, even for your most complex calculations. Move faster, collaborate more effectively, and make smarter decisions. *** ## Easily query right in your sheet With a built-in intuitive query builder integrated directly into [Google Sheets](https://docs.getdbt.com/docs/cloud-integrations/semantic-layer/gsheets) and [Microsoft Excel](https://docs.getdbt.com/docs/cloud-integrations/semantic-layer/excel), users can retrieve the metrics they need, apply filters, and enable pivot tables or custom formulas with accurate, up-to-date data — no SQL required. [Book a demo](https://www.getdbt.com/contact) | [See integrations](https://www.getdbt.com/product/integrations) *** ## Trust your analysis with fresh, consistent metrics Metrics like "Year-over-Year Revenue Growth" are standardized in dbt Semantic Layer, providing a single source of truth for metrics across spreadsheets, reducing errors and eliminating redundancy. Real-time or scheduled updates keep spreadsheets accurate and reliable, saving hours of manual work. [About dbt Semantic Layer](https://www.getdbt.com/product/semantic-layer) | [Book a demo](https://www.getdbt.com/contact) *** ## Fast insights, no matter the complexity Features like common query caching on live data reduce latency and improve speed, allowing teams to quickly generate insights from even the most complex datasets. Spend less time managing data infrastructure and more time on analysis. [Learn more about query optimization](https://docs.getdbt.com/docs/use-dbt-semantic-layer/sl-cache) *** ## See the full picture — from raw data to insights With the dbt Semantic Layer built on top of dbt models, you get end-to-end lineage with full DAG visibility, tracing every metric back to its source for total transparency, accuracy, and trust. [Book a demo](https://www.getdbt.com/contact) | [Try dbt free](https://www.getdbt.com/signup) *** ## Learn more about dbt ### Five use cases for the dbt Semantic Layer From AI to BI to embedded apps, learn how to deliver trusted data to any endpoint [Read the blog](https://www.getdbt.com/blog/five-use-cases-for-the-dbt-semantic-layer) ### Semantic Layer: What it is and when to adopt it The explosion of data sources can make it harder for employees to find, trust, and use data. Here's how a semantic layer can help [Read the blog](https://www.getdbt.com/blog/semantic-layer-introduction) ### How Bilt Rewards delivered personalized analytics See how Bilt Rewards used dbt's Semantic Layer to embed personalized insights and enable a more efficient, trusted analytics environment. [Watch the session](https://www.youtube.com/watch?v=6vQ_VsXDGFc) *** ## Start building with dbt Streamline your data transformation process, reduce manual errors, and increase productivity with dbt. Sign up today and take your data transformation workflow to the next level. [Try dbt today](https://www.getdbt.com/signup) | [Book a demo](https://www.getdbt.com/contact) --- --- title: "Subcontractor BAA" description: "Review dbt Labs’ Subcontractor Business Associate Agreement outlining HIPAA-compliant data handling and security obligations." url: "https://www.getdbt.com/subcontractor-baa" --- # Subcontractor BAA *** **SUBCONTRACTOR BUSINESS ASSOCIATE AGREEMENT** **THIS BUSINESS ASSOCIATE AGREEMENT** (“**BAA**”) is entered into between dbt Labs, Inc. (“**Client**”) and the entity (“**Business Associate**”) that entered into an underlying master agreement with Client that references this BAA, including any active statements of work, in each case as updated from time to time (“**Agreement**”). This BAA supplements the Agreement and is effective as of the same date as the Agreement. Business Associate and Client may be individually referred to as a “**party**” and, collectively, the “**parties**” in this BAA. Client may be the business associate or subcontractor of one or more Covered Entities or have a relationship to one or more entities in such relationships to one or more Covered Entities (“**End-Clients**”). To the extent Business Associate performs certain functions or activities that involve the use or disclosure of any individual’s or Covered Entity’s PHI through its services as a business associate or subcontractor of Client (“**Use**”), this BAA applies to such Use provided applicable law as referenced herein requires the parties to enter into such a BAA. (A) Business Associate is providing services to Client under an underlying agreement (“**Agreement**”), and Client or End-Clients may wish to disclose certain information to Business Associate pursuant to the terms of such Agreement, some of which may constitute Protected Health Information (PHI) under the Health Insurance Portability and Accountability Act of 1996, as amended (“**HIPAA**”), and the Privacy Rule, Security Rule, Enforcement Rule and Breach Notification Rule set forth at 45 C.F.R. Parts 160 and 164 and the Health Information Technology for Economic and Clinical Health Act § 13400 (“**HITECH**”) and any related implementing regulations and guidance (jointly, the “**HIPAA** **Rules**”) promulgated thereunder. (B) Business Associate may create, maintain, access, use, disclose, transmit or receive PHI on behalf of Client only as set forth in this BAA and to the extent allowed under the HIPAA Rules. (C) Client, End-Clients, and Business Associate intend to protect the privacy and provide for the security of PHI in compliance with HIPAA and the HIPAA Rules. (D) The purpose of this BAA is to satisfy certain standards and requirements of HIPAA and the HIPAA Rules, including, but not limited to, Title 45, §§ 164.314(a)(2)(i), 164.502(e) and 164.504(e) of the Code of Federal Regulations (C.F.R.). Accordingly, the parties hereto agree as follows: **1. DEFINITIONS** “**Capitalized Terms**”. Capitalized terms used in this BAA and not otherwise defined herein has the meanings set forth in the HIPAA Rules, which definitions are incorporated in this BAA by reference. “**Protected Health Information**”or “**PHI**”has the same meaning given to such term in 45 C.F.R. § 160.103, as applied to the protected health information created, received, maintained or transmitted by Business Associate from or on behalf of Client. “**Unsuccessful Security Incident**” means pings and other broadcast attacks on a firewall, port scans, unsuccessful log-on attempts, denials of service, or other similar attempted but unsuccessful Security Incident, or a combination thereof, so long as no such incident results in unauthorized access, use or disclosure of PHI. **2. PERMITTED USES AND DISCLOSURES OF PHI** i. Uses and Disclosures of PHI Pursuant to the Agreement. Business Associate shall not use or disclose PHI other than as permitted or required to perform functions, activities, or services for, or on behalf of, Client and/or End-Clients as specified in the Agreement or as Required by Law, provided that such use or disclosure would not violate the Privacy Rule if done by Client and/or End-Clients, except as set forth in Sections 2(ii) and 2(iii) of this BAA. To the extent Business Associate is carrying out any of Client’s and/or End-Clients’ obligations under the Privacy Rule pursuant to the terms of the Agreement or this BAA, Business Associate shall comply with the requirements of the Privacy Rule that apply to Client and/or End-Clients in the performance of such obligation(s). To the extent Client is subject to policies related to PHI of End-Clients not parties hereto, Business Associate will use commercially reasonable efforts to comply with any End-Client’s policies provided those policies and procedures do not conflict with law or with Business Associate’s policies. ii. Permitted Uses of PHI by Business Associate. Except as otherwise limited in this BAA, Business Associate may use PHI for the proper management and administration of Business Associate or to carry out the legal responsibilities of Business Associate. iii. Permitted Disclosures of PHI by Business Associate. Except as otherwise limited in this BAA, Business Associate may disclose PHI for the proper management and administration of Business Associate, provided that the disclosures are Required by Law, or Business Associate obtains reasonable assurances from the person to whom the information is disclosed that it is to remain confidential and will be used or further disclosed only as Required by Law or for the purpose for which it was disclosed to the person (which purpose must be consistent with the limitations imposed upon Business Associate pursuant to this BAA), and that the person agrees to notify Business Associate of any instances of which it is aware in which the confidentiality of the information has been breached. **3. OBLIGATIONS OF BUSINESS ASSOCIATE** i. Appropriate Safeguards. Business Associate shall use appropriate safeguards and shall comply with the Security Rule with respect to Electronic PHI, to prevent use or disclosure of such information other than as provided for by the Agreement and this BAA. Business Associate shall implement and maintain a risk analysis and risk management program to assess and address potential risks and vulnerabilities to the confidentiality, integrity, and availability of Electronic PHI. ii. Reporting of Improper Use or Disclosure, Security Incident or Breach. Business Associate shall report to Client any use or disclosure of PHI not permitted under this BAA, Breach of Unsecured PHI or Security Incident, without unreasonable delay, pursuant to the requirements of 45 CFR §§ 164.404–410, and in any event no more than 3 business days following discovery; provided, however, that the parties acknowledge and agree that this Section constitutes notice by Business Associate to Client of the ongoing existence and occurrence of Unsuccessful Security Incidents. iii. Business Associate’s Agents. In accordance with 45 C.F.R. § 164.502(e)(1)(ii) and 45 C.F.R. § 164.308(b)(2), as applicable, Business Associate shall enter into a written agreement with any agent or subcontractor that creates, receives, maintains, or transmits PHI on behalf of Business Associate for services provided to Client, providing that the subcontractor or agent agrees to substantially the same restrictions and conditions that apply to Business Associate through this BAA with respect to such PHI. Neither Business Associate nor its agents or subcontractors will sell PHI under any circumstances. iv. Access to PHI. To the extent Business Associate has PHI on its systems, Business Associate agrees to cooperate with reasonable requests for assistance by Client and to make information available to Client to enable Client to comply with 45 C.F.R. § 164.524. v. Amendment of PHI. To the extent Business Associate has PHI on its systems, Business Associate agrees to make such information available to Client for amendment pursuant to 45 C.F.R. § 164.526. vi. Documentation of Disclosures. To the extent Business Associate has PHI on its systems, Business Associate agrees to document such disclosures of PHI and information related to such disclosures as would be required for Client to respond to a request by an Individual for an accounting of disclosures of PHI in accordance with 45 C.F.R. § 164.528. vii. Accounting of Disclosures. To the extent Business Associate has PHI on its systems, Business Associate agrees to provide to Client, upon receipt of a written request from Client, information collected in accordance with Section 3(vi) of this BAA to permit Client to respond to a request by an Individual for an accounting of disclosures of PHI in accordance with 45 C.F.R. § 164.528. viii. Governmental Access to Records. Business Associate shall make its internal practices, books and records relating to the use and disclosure of PHI received from, or created or received by Business Associate on behalf of, Client available to the Secretary for purposes of the Secretary determining Client’s compliance with the Privacy Rule. ix. Mitigation. To the extent practicable, Business Associate will reasonably cooperate with Client’s efforts to mitigate a harmful effect that is known to Business Associate of a use or disclosure of PHI by Business Associate that is not permitted by this BAA. Such mitigation efforts shall comply with the obligations of 45 CFR § 164.530, the direction of HHS, and the requirements of any other governmental agency with applicable authority. x. Minimum Necessary. Business Associate shall request, use and disclose the minimum amount of PHI necessary to accomplish the purpose of the request, use or disclosure, in accordance with 45 C.F.R. § 164.514(d), and any amendments thereto. Business Associate will not disclose PHI related to reproductive health care in response to requests from law enforcement, regulatory, or oversight agencies, or any third parties unless the requestor provides a written attestation confirming the PHI will not be used to investigate or penalize lawful reproductive health care activities, as required by 45 CFR 164.502(a)(5)(ii). Business Associate must document and retain the attestation. Business Associate shall provide a copy or proof of the documented attestation at the reasonable request of Client. **4. OBLIGATIONS OF CLIENT** i. Notice of Privacy Practices. Client shall notify Business Associate of any limitation(s) in its, or an applicable, Notice of Privacy Practices in accordance with 45 C.F.R. § 164.520, to the extent that such limitation may affect Business Associate’s use or disclosure of PHI. ii. Notification of Changes Regarding Individual Permission. To the extent Client receives PHI directly from the individual, Client shall obtain any consent or authorization that may be required by the Privacy Rule, or applicable state law, prior to furnishing Business Associate with PHI. If applicable, Client shall notify Business Associate of any changes in, or revocation of, permission by an Individual, or other entities providing such PHI, to use or disclose PHI, to the extent that such changes may affect Business Associate’s use or disclosure of PHI. **5. TERM AND TERMINATION** i. Term. This BAA terminates when all of the PHI provided by Client and/or End-Clients to Business Associate, or created or received by Business Associate on behalf of Client, is destroyed or returned to Client and/or End-Clients. If it is infeasible to return or destroy PHI, Business Associate shall extend protections to such information in accordance with Section 5(iii). ii. Termination for Cause. Upon either party’s knowledge of a material breach by the other party of this BAA, such party may terminate this BAA immediately if cure is not possible. Otherwise, the non-breaching party shall provide written notice to the breaching party detailing the nature of the breach and providing an opportunity to cure the breach within 30 business days. Upon the expiration of such 30-day cure period, the non-breaching party may terminate this BAA if the breaching party does not cure the breach or if cure is not possible. iii. Effect of Termination. 1. Except as provided in Section 5(iii)(2), within two (2) business days of termination of the Agreement or this BAA for any reason, Business Associate shall return or destroy all PHI on its systems received from Client and/or End-Clients, or created or received by Business Associate on behalf of Client and/or End-Clients, and shall retain no copies of the PHI. 2. If Business Associate determines that it is infeasible to return or destroy the PHI upon termination of the Agreement or this BAA (e.g., retention of PHI is necessary to continue Business Associate’s proper management and administration or to carry out Business Associate’s legal obligations), Business Associate shall give notice to Client and any End-Clients who provided the PHI directly to Business Associate and: (a) extend the protections of this BAA to such PHI and (b) limit further uses and disclosures of such PHI to those purposes that make the return or destruction infeasible, for so long as Business Associate maintains such PHI. **6. COOPERATION IN INVESTIGATIONS** The parties acknowledge that certain breaches or violations of this BAA may result in litigation or investigations pursued by federal or state governmental authorities of the United States resulting in civil liability or criminal penalties. Each party shall give notice of any contact or requests by such authorities and cooperate in good faith in all respects with the other party and/or End-Clients in connection with any request by a federal or state governmental authority for additional information and documents or any governmental investigation, complaint, action or other inquiry. **7. SURVIVAL** The respective rights and obligations of Business Associate under Section 5(iii) of this BAA survive the termination of this BAA and the Agreement until resolved. **8. AMENDMENT** This BAA may be modified to by Client to address legal or regulatory changes in HIPAA Rules, but no rights may be waived without a document executed by the authorized representatives of both parties. In addition, if any relevant provision of the HIPAA Rules is amended in a manner that changes the obligations of Business Associate or Client and/or End-Clients that are embodied in terms of this BAA, then the parties agree to negotiate in good faith appropriate non-financial terms or amendments to this BAA to give effect to such revised obligations. **9. EFFECT OF BAA** In the event of any inconsistency between the provisions of this BAA and the Agreement, the provisions of this BAA control. In the event that a court or regulatory agency with authority over Business Associate, Client, and/or End-Clients interprets the mandatory provisions of the HIPAA Rules, in a way that is inconsistent with the provisions of this BAA, such interpretation controls. Where provisions of this BAA are different from those mandated in the HIPAA Rules, but are nonetheless permitted by such rules as interpreted by courts or agencies, the provisions of this BAA shall control. **10. GENERAL** Any disputes arising under this BAA are governed by the laws of the State that govern the Agreement. Client shall not assign this BAA without the prior written consent of Business Associate, which shall not be unreasonably withheld. If any part of a provision of this BAA is found illegal or unenforceable, it will be enforced to the maximum extent permissible, and the legality and enforceability of the remainder of that provision and all other provisions of this BAA are not affected. All notices relating to the parties’ legal rights and remedies under this BAA will be provided in writing to a party, will be sent to its address below or as set forth in the Agreement, or to such other address as may be designated by that party by notice to the sending party, and will reference this BAA. Any notice to Client will be effective if copied to [legal@dbtlabs.com](mailto:legal@dbtlabs.com). If End-Clients provide PHI directly to Business Associate, Business Associate will be responsible for identifying End-Clients’ notice address(es). Nothing in this BAA confers any right, remedy, or obligation upon anyone other than Client and Business Associate. This BAA is the complete and exclusive agreement between the parties with respect to the subject matter hereof, superseding and replacing all prior agreements, communications, and understandings (written and oral) regarding its subject matter. **11. INDEPENDENT CONTRACTOR** Business Associate is, for all purposes, an independent contractor, and Business Associate will not, directly or indirectly, act as agent, servant or employee of Client and/or End-Clients or make any commitments or incur any liabilities on behalf of Client and/or End-Clients without express written consent. Nothing in this BAA creates an employment, principal-agent or partner relationship between the parties. Business Associate retains sole and absolute discretion in the manner and means of carrying out its activities and responsibilities under this BAA. _Last Updated May 19, 2025_ --- --- title: "Subcontractor DPA" description: "Review dbt Labs’ Subcontractor Data Processing Addendum outlining data handling, compliance, and security obligations for subcontracted services." url: "https://www.getdbt.com/subcontractor-dpa" --- # Subcontractor DPA *** **SUBCONTRACTOR DATA PROCESSING ADDENDUM** This Subcontractor Data Processing Addendum (“**DPA**”) governing the use by dbt Labs, Inc. (“**dbt Labs**”) and clients of dbt Labs acting as controllers (dbt Labs together with its relevant clients, “**Customer**”) of the Services, between dbt Labs and the entity (“**SUBCONTRACTOR**”) that entered into an underlying master agreement with dbt Labs that references this DPA, including any active statements of work (“**SOWs**”), in each case as updated from time to time (“**Agreement**”). This DPA supplements the Agreement, has the same effective date (“**Effective Date**”) as the Agreement, and governs SUBCONTRACTOR’s access to and processing, retention, and/or use of Customer Data pursuant to Applicable Law. Unless otherwise defined in this DPA or in the Agreement, all capitalised terms used in this DPA will have the meanings given to them in Section 17 of this DPA. **1. Data Processing.** **1.1 Scope and Roles.** This DPA applies when Customer Data is processed by SUBCONTRACTOR. In this context, SUBCONTRACTOR will act as processor to Customer, who can act either as controller or processor of Customer Data. **1.2 Details of Data Processing.** 1.2.1 **Subject matter.** The subject matter of the data processing under this DPA is Customer Data. 1.2.2 **Duration.** As between SUBCONTRACTOR and Customer, the duration of the data processing under this DPA is determined by Customer. 1.2.3 **Purpose.** The purpose of the data processing under this DPA is the provision of the Services initiated by Customer from time to time. 1.2.4 **Nature of the processing.** Compute, storage and such other Services as described in the Documentation and initiated by Customer from time to time. 1.2.5 **Type of Customer Data.** Customer Data uploaded, provided, transferred or made accessible to SUBCONTRACTOR by Customer. 1.2.6 **Categories of data subjects.** The data subjects could include Customer’s clients, employees, contractors, agents, designees, suppliers and End Users. **1.3 Compliance with Laws**. SUBCONTRACTOR will comply with all laws, rules and regulations (together with data protection and privacy laws, including without limitation the GDPR, the CCPA, other State Laws, and any law, statute, declaration, decree, directive, legislative enactment, order, ordinance, regulation, rule or other binding instrument which implements any of the above or which otherwise relates to data protection, privacy or the use of Personal Data and incorporating any amendments, revisions or modifications, “**Applicable Law**”) applicable and binding on it in the performance of this DPA. **1.4 Ownership and Access**. SUBCONTRACTOR agrees that Customer owns all rights to Customer Data. Except to comply with the Subcontractor Security Standards, SUBCONTRACTOR will not under any circumstances impede, prevent, restrict, block or deny access of Customer to Customer Data. **2. Customer Instructions.** The parties agree that this DPA, the Agreement, and Customer provided instructions via Services constitute Customer’s instructions regarding SUBCONTRACTOR’s processing of Customer Data (“**Instructions**”). SUBCONTRACTOR will process Customer Data only in accordance with Instructions. SUBCONTRACTOR acknowledges that where Customer is acting as a processor, these may be based on the instructions of its controllers. Lawful instructions from dbt Labs’ controllers will be accepted by SUBCONTRACTOR, and SUBCONTRACTOR will process Customer Data according to such instructions. SUBCONTRACTOR will not retain, use, or disclose Customer Data outside the direct business relationship between SUBCONTRACTOR and Customer, including by not combining any Customer Data with other personal information collected or received from any other source, except as permitted by the CCPA; and SUBCONTRACTOR will not sell or share Customer Data or take any action that will place Customer in violation of any Applicable Law. If SUBCONTRACTOR reasonably believes that processing pursuant to Instructions is likely to violate Applicable Law, SUBCONTRACTOR will inform Customer without undue delay, in which event, Customer is entitled to withdraw or modify its Instructions. Customer is entitled to terminate this DPA and the Agreement if SUBCONTRACTOR declines to process pursuant to Customer’s lawful instructions hereunder. Processing outside the scope of this DPA will require a prior written agreement between the Customer and SUBCONTRACTOR. **3. Confidentiality of Customer Data.** SUBCONTRACTOR will not access or use, or disclose to any third party, any Customer Data, except, in each case, as necessary to perform the Services, or as necessary to comply with the law or a valid and binding order of a governmental body (such as a subpoena or court order). If a governmental body sends SUBCONTRACTOR a demand for Customer Data, SUBCONTRACTOR will attempt to redirect the governmental body to request that data directly from Customer. As part of this effort, SUBCONTRACTOR may provide Customer’s basic business contact information to the governmental body. If compelled to disclose Customer Data to a governmental body, then SUBCONTRACTOR will give Customer reasonable notice of the demand to allow Customer to seek a protective order or other appropriate remedy unless SUBCONTRACTOR is legally prohibited from doing so. **4. Confidentiality Obligations of Subcontractor Personnel.** During the term hereof,SUBCONTRACTOR will implement and maintain control that restrict its personnel from processing Customer Data without authorisation by SUBCONTRACTOR pursuant to the Subcontractor Security Standards. SUBCONTRACTOR provides appropriate training annually and procures appropriate contractual obligations of its personnel that effectuate its confidentiality, data protection and data security obligations. **5. Security of Data Processing** **5.1** **Technical and Organisational Measures**. Taking into account the state of the art, the costs of implementation and the nature, scope, context and purposes of processing, as well as the risk of varying likelihood and severity for the rights and freedoms of natural persons, SUBCONTRACTOR has implemented and will maintain or exceed appropriate technical and organisational measures to ensure a level of security appropriate to the risk, including the measures set out in the Subcontractor Security Standards. **5.2** **Subcontractor Employees and Personnel.** SUBCONTRACTOR shall ensure that any employees or other personnel have agreed in writing to protect the confidentiality and security of Customer Data (as applicable). **6. Subprocessing.** **6.1 Authorised Subprocessors.** Customer provides general authorisation to SUBCONTRACTOR’s use of subprocessors to provide lawful processing activities on Customer Data on behalf of Customer (“**Subprocessors**”) in accordance with this Section 6 to the extent SUBCONTRACTOR notifies Customer within 30 days of the Effective Date of this DPA, identifies Subprocessors that SUBCONTRACTOR currently engages, and specifies the Subprocessor’s name and address, the services provided, and the region in which the Subprocessor provides its services. Customer may object to the engagement of any such initial Subprocessor for a period of 30 days after receiving such notice from SUBCONTRACTOR. Additionally, at least 60 days before SUBCONTRACTOR engages an additional or new Subprocessor, SUBCONTRACTOR will notify dbt Labs of the proposed change, and Customer may object to the engagement of any such additional or new Subprocessor during such 60 day period. Where Customer objects to a Subprocessor, (a) SUBCONTRACTOR may propose moving the relevant Customer Data to an alternate Subprocessor and (b) SUBCONTRACTOR shall, within a reasonable time following receipt of such written request, use commercially reasonable efforts to ensure that the Subprocessor does not process any of the Customer Data until the move, or if such alternate Subprocessor is not feasible, available and/or acceptable to Customer, Customer may: (i) terminate the Agreement for breach pursuant to its terms; (ii) cease using the affected part of the Service for which SUBCONTRACTOR has engaged the Subprocessor; or (iii) change to an alternate SUBCONTRACTOR Region where SUBCONTRACTOR has not engaged the Subprocessor. **6.2 Subprocessor Obligations.** Where SUBCONTRACTOR authorises a Subprocessor as described in Section 6.1: (i) SUBCONTRACTOR will restrict the Subprocessor’s access to Customer Data only to what is necessary to provide or maintain the Services in accordance with the Documentation, and SUBCONTRACTOR will prohibit the Subprocessor from accessing Customer Data for any other purpose; (ii) SUBCONTRACTOR will enter into a written agreement with the Subprocessor and, to the extent that the Subprocessor performs SUBCONTRACTOR’s data processing hereunder or under the Agreement, SUBCONTRACTOR will impose on the Subprocessor substantially similar contractual obligations that SUBCONTRACTOR has under this DPA and the Agreement; and (iii) SUBCONTRACTOR will remain responsible for compliance with its obligations under this DPA and for any acts or omissions of the Subprocessor as if they were the acts and omissions of SUBCONTRACTOR. **7. Subcontractor Assistance with Data Subject Requests.** SUBCONTRACTOR will assist Customer in fulfilling reasonable requests by Customer for assistance meeting its obligations to respond to data subjects’ requests under the Applicable Law. If a data subject makes a request to SUBCONTRACTOR, SUBCONTRACTOR will forward such request to Customer without undue delay once SUBCONTRACTOR has identified that the request is from a data subject for whom Customer is responsible. **8. CPRA Cooperation.** To the extent legally required, with respect to Customer Data on its systems, SUBCONTRACTOR will cooperate with Customer in responding to verifiable consumer requests by, for example: (a) providing responsive personal information in its possession obtained during the relationship to Customer; (b) deleting Customer Data and, if applicable, notifying downstream entities about the deletion request; and (c) permitting the correction of inaccurate information. **9. Security Incident Notification.** **9.1 Security Incident.** SUBCONTRACTOR will (a) notify Customer of a Security Incident within twenty-four (24) hours after becoming aware of the Security Incident, and (b) investigate the Security Incident and provide such reasonable assistance to the Customer (and any law enforcement or Regulator) as required to investigate the Security Incident, (c) take steps to remedy any noncompliance by SUBCONTRACTOR with this DPA, and (d) take any other measures appropriate to address the Security Incident, including without limitation measures reasonably requested by Customer to remediate and mitigate any adverse effects resulting from the Security Incident. **9.2 Subcontractor Assistance.** To enable Customer to provide notice of a Security Incident to supervisory authorities or data subjects (as applicable), SUBCONTRACTOR will cooperate with and assist Customer by including in the notification under Section 9.1 (a) such information about the Security Incident as SUBCONTRACTOR is able to disclose to Customer, taking into account the nature of the processing, the information available to SUBCONTRACTOR, and any restrictions on disclosing the information, such as confidentiality. **9.3 Unsuccessful Security Incidents.** Customer agrees that an unsuccessful Security Incident will not be subject to this Section 9. An unsuccessful Security Incident is one that results in no unauthorised access to Customer Data or to any of SUBCONTRACTOR’s equipment or facilities storing Customer Data, and could include, without limitation, pings and other broadcast attacks on firewalls or edge servers, port scans, unsuccessful log-on attempts, denial of service attacks, packet sniffing (or other unauthorised access to traffic data that does not result in access beyond headers) or similar incidents. **9.4 Communication.** Notification(s) of Security Incidents, if any, will be delivered via email to one or more of Customer’s contacts or administrators, an additional copy sent to legal@dbtlabs.com. **10. Subcontractor Certifications and Audits.** **10.1 Subcontractor ISO-Certification, SOC Reports and Vulnerability Testing.** Upon Company’s request, and provided that the parties have an applicable NDA in place, Subcontractor will make available at a minimum the following documents and information: (i) the certificates issued for ISO 27001 and the ISO 27701 or the international equivalent; (ii) the System and Organization Controls (SOC) 2 Type II Report and HIPAA Report or the international equivalent; (iii) a business continuity plan that aligns with industry standards; (iv) evidence of periodic (but at least annually), manual and automated vulnerability testing by an accredited third party performed (including penetration testing based on recognized industry best practices) on all Subcontractor internet-facing networks, systems, software, and devices used to access Company Data, which shall include a statement of opinion from an accredited third party for vulnerability and penetration testing completed on Subcontractor internet facing systems; and Subcontractor further agrees that Subcontractor will notify Company within 72 hours if Subcontractor identifies a vulnerability that has been compromised and is a risk to Company’s implementation of any Services or Deliverables provided by Subcontractor to Company under the Agreement and will promptly provide remediation steps and patching instructions to address the vulnerability and risk; and (v) other reports/documentation describing controls implemented by Subcontractor that update, replace or are substantially equivalent to such certificates, plans, and/or reports. **10.2 Subcontractor Annual Audits.** SUBCONTRACTOR’s use of external auditors will verify the adequacy of its security measures, including the security of any physical locations from which SUBCONTRACTOR provides the Services, if applicable. Audits: (a) will be performed at least annually; (b) will be performed according to ISO 27001 standards or such other alternative standards that are substantially equivalent to ISO 27001; (c) will be performed by independent third party security professionals at SUBCONTRACTOR’s selection and expense; and (d) will result in the generation of an audit report (“**Report**”), which will be SUBCONTRACTOR’s Confidential Information. **10.3 Audit Reports.** At Customer’s written request, and provided that the parties have written confidentiality protections in place, SUBCONTRACTOR will provide Customer with a copy of the Report so that Customer can reasonably confirm SUBCONTRACTOR’s compliance with its obligations under this DPA. **10.4 Privacy Impact Assessment and Prior Consultation.** Taking into account the nature of the processing and the information available to SUBCONTRACTOR, SUBCONTRACTOR will assist Customer in complying with Customer’s obligations in respect of data protection impact assessments and prior consultation, by providing the information SUBCONTRACTOR makes available under this Section 10. **11. Customer Audits.** SUBCONTRACTOR will, upon reasonable prior written request from the Customer, allow for and contribute to inspections and/or audits, including providing relevant information reasonably requested as necessary to demonstrate SUBCONTRACTOR’s compliance with Applicable Law, this DPA and/or inspections, and conducted by Customer or an independent third party auditor appointed by Customer, in possession of the required professional qualifications and bound by a duty of confidentiality provided (i) such audits or inspections are not conducted more than once per year (unless required by a Regulator or in the event of a Security Incident); (ii) are conducted only during normal business hours; and (iii) are limited to determining compliance by SUBCONTRACTOR with its obligations hereunder. SUBCONTRACTOR shall reimburse Customer any reasonable fees or costs incurred by Customer in conducting (or arranging the conduct of) any audits where SUBCONTRACTOR is found by Customer or the independent auditor, acting reasonably, to be in material violation of this DPA. **12. Transfers of Personal Data.** **12.1 Regions.** If available and applicable as indicated in the SOW, ordering document and/or Agreement, Customer can specify a certain limited geographical location where Customer Data will be processed (“**Region**”), including without limitation Regions in the EEA (Germany), the U.S. (Virginia), or Australia (Sydney). In such event, SUBCONTRACTOR will not transfer Customer Data from the selected Region except to an authorised Subprocessor or as directed by Customer, as permitted in writing by Customer, or as necessary to comply with the law or binding order of a governmental body. **12.2 Application of Standard Contractual Clauses.** Subject to Section 12.3 and to the extent SUBCONTRACTOR (acting as a data importer) processes Customer Data in a Third Country ( “**Data Transfer**”), SUBCONTRACTOR shall, and shall procure that any of its affiliates, contractors, and Subprocessors shall, comply with the data importer’s obligations set out in the Controller to Processor Clauses, which are hereby incorporated into and form part of this DPA. 12.2.1 When Customer is acting as a controller, the Controller-to-Processor Clauses will apply to a Data Transfer. Customer will comply with the data exporter’s obligations in such Controller to Processor Clauses. 12.2.2 Where dbt Labs acts as a processor, the Processor-to-Processor Clauses may apply to a Data Transfer. dbt Labs acknowledges that it may not be possible for SUBCONTRACTOR to know the identity of dbt Labs’s controllers because SUBCONTRACTOR may have no direct relationship with dbt Labs’s controllers; and, therefore, in such a circumstance, dbt Labs may fulfil SUBCONTRACTOR’s obligations to dbt Labs’s controllers under SCCs between dbt Labs and its controllers, where legally required and/or applicable. In the alternative, where SUBCONTRACTOR knows the identity of dbt Labs’s controllers, SUBCONTRACTOR will fulfil its obligations to Customer. 12.2.3 With respect to any Standard Contractual Clauses required by law of the parties, the parties will negotiate in good faith to determine the appropriate template and agree upon its provisions, and the appropriate template will be deemed to be executed as of the date hereof. Further, with respect to the GDPR Controller to Processor Clauses, as applicable (and adapted as necessary or required by law): (a) for the purposes of Annex I.A of such Controller to Processor Clauses, the Data Exporter is a data controller and the Data Importer is a data processor, and the name, address, contact person’s details and relevant activities for each of them is as set out in the Agreement; (b) for the purposes of Appendix 1 or Annex I/I.B (as relevant) of such Controller to Processor Clauses, Section 1.2 of this DPA shall apply; (c) for the purposes of Appendix 2 of Annex II (as relevant) of such Controller to Processor Clauses, the security measures set out in Annexes I and II of this DPA shall apply; and (d) if applicable, for the purposes of: (i) Clause 7 (Docking Clause), this is optional and deleted; (ii) Clause 9 of such Controller to Processor Clauses, Option 2 (“General written authorization”) is deemed to be selected and the notice period specified in Section 9.1 of this DPA shall apply; (iii) clause 11(a) of such Controller to Processor Clauses, the optional wording in relation to independent dispute resolution is deemed to be omitted; (iv) Clause 13 (a) (First Paragraph Option) and Annex I.C, the competent supervisory authority shall be the supervisory authority of the EU member state where the Subscriber is established or where its local representative is appointed; (v) Clause 17, Option 1 is deemed to be selected and the governing law shall be Ireland and (vi) Clause 18, the competent courts shall be Ireland. **12.3 Alternative Transfer Mechanism.** The Standard Contractual Clauses will not apply to a Data Transfer if SUBCONTRACTOR has adopted Binding Corporate Rules for Processors or an alternative recognised compliance standard for lawful Data Transfers. **12.4 Subprocessor Compliance**. To the extent SUBCONTRACTOR permits Subprocessors to Process Customer Data in any Third Country: (a) SUBCONTRACTOR shall execute the Processor to Processor Clauses, where applicable, with any relevant sub-processor or subcontractor it appoints on behalf of the Customer; or (b) if the Processor to Processor Clauses are not applicable, the parties agree to execute the relevant Controller to Processor Clauses with the processing details set out in Section 1.2 of this DPA shall apply to Appendix 1 and the technical and organizational measures set out in Annexes I and II of this DPA shall apply to Appendix 2, with any relevant Subprocessor it appoints on behalf of the Customer. **12.5 Conflicts**. In the event of any conflict between any terms herein or those required in Applicable Law, this DPA and the Agreement, the terms required by Applicable Law shall be deemed incorporated herein and shall prevail over any conflicting language. **13. Termination of the DPA.** This DPA will continue in force until the termination of the Agreement (“**Termination Date**”). Upon the Termination Date, SUBCONTRACTOR will cease Processing Customer Data on behalf of Customer except to the extent required for SUBCONTRACTOR to comply with Section 14 hereof. **14. Return or Deletion of Customer Data**. Customer Data will be retained by Subcontractor only for so long as it is reasonably required to provide Services and comply with obligations under the Agreement. Upon written request by Customer or at least within 21 days following the Termination Date, subject to the terms and conditions of the Agreement, SUBCONTRACTOR will return or delete Customer Data, without undue delay, except as required for legal, fiduciary or tax purposes or by SUBCONTRACTOR’s consultants, advisors, auditors, attorneys, investors, bankers, payment processors, regulatory bodies, tax authorities, when compelled by court order, or as otherwise needed to fulfill SUBCONTRACTOR’s duties under this Agreement. Any Customer Data so retained will remain subject to the confidentiality provisions herein and in the Agreement and will be used solely by SUBCONTRACTOR for such purposes as described herein until returned or deleted, and such confidentiality obligations will survive termination or expiration hereof. **15. Duties to Inform.** **15.1 Insolvency.** Where Customer Data becomes subject to confiscation during bankruptcy or insolvency proceedings, or similar measures by third parties while being processed by SUBCONTRACTOR, SUBCONTRACTOR will inform Customer without undue delay. SUBCONTRACTOR will, without undue delay, notify such parties (for example, creditors, bankruptcy trustee) that Customer Data is Customer’s property and responsibility and that Customer Data is at Customer’s sole disposition. **15.2 Changes in Law**. The parties agree to notify the other party of any changes in Applicable Law requiring modification to this DPA, and the parties agree negotiate in good faith modifications to this DPA if changes are required for SUBCONTRACTOR to continue to process Customer Data as contemplated by this DPA in compliance with the Applicable Law or to address the legal interpretation of the Applicable Law, including without limitation (i) any guidance on the interpretation of any of their respective provisions; (ii) the Standard Contractual Clauses or any other mechanisms or findings of adequacy are issued, invalidated or amended, or (iii) if changes to the membership status of a country in the European Union or the European Economic Area require such modification. **16. Entire Agreement; Conflict**. This DPA incorporates the Standard Contractual Clauses by reference. This DPA will replace any previously applicable data processing addendum dated prior to the date hereof. Except as amended by this DPA, the Agreement will remain in full force and effect. In the event of a conflict between the Agreement and this DPA, the terms of this DPA will control as to matters related to data protection, data privacy, and Applicable Law but not trade laws. Nothing in this document varies or modifies the Standard Contractual Clauses. **17. Definitions.** Unless otherwise defined in the Agreement, all capitalised terms used in this DPA will have the meanings given to them below: “**CCPA**” means the California Consumer Privacy Act of 2018 as updated by the California Privacy Rights Act of 2020 (“**CPRA**”), including any regulations promulgated thereunder, as amended from time to time. The terms “**controller**”, “**data subject**”, “**Personal Data**”, “**processor**”, and “**process**” (and their conjugates) shall have the same meaning as set out in the GDPR whether or not European or non-European Data Protection Laws apply. The terms “**business**”, “**Service Provider**”, “**share**” and “**sell**” (and their conjugates) shall have the same meaning as set out in the CCPA/CPRA. “**Controller-to-Processor Clauses**” means the standard contractual clauses between controllers and processors for Data Transfers, as approved by the European Commission Implementing Decision (EU) 2021/914 of 4 June 2021. “**Customer Data**” means Personal Data uploaded, provided, transferred or made accessible to SUBCONTRACTOR by Customer. “**EEA**” means the European Economic Area. “**GDPR**” means Regulation 2016/679 of the European Parliament and of the Council of 27 April 2016 on the protection of natural persons with regard to the processing of Personal Data and on the free movement of such data, and repealing Directive 95/46/EC (General Data Protection Regulation). For purposes of this DPA, GDPR shall also encompass other European laws, in each case as amended and replaced from time to time and to the extent applicable, including but not limited to the Privacy and Electronic Communications Directive 2002/58/EC; the UK Data Protection Act 2018, the UK General Data Protection Regulation as amended by the Data Protection, Privacy and Electronic Communications (Amendments etc) (EU Exit) Regulations 2019, and the Privacy and Electronic Communications Regulations 2003; and the Swiss Federal Act on Data Protection. Any reference to the SCCs herein shall be interpreted to be the clauses required by the applicable country or region governing the Personal Data. Where more than one jurisdiction governs Personal Data, the laws of the jurisdiction that is most protective shall prevail as to the SCCs that apply. “**Other State Laws**” means, once enforced, the applicable laws and regulations enacted by and in effect in any other U.S. states and/or the U.S. Federal government, as amended or replaced from time to time, including but not limited to Connecticut, Illinois, Virginia, Colorado, Texas, and Utah. **“Processor-to-Processor Clauses”** means the standard contractual clauses between processors for Data Transfers, as approved by the European Commission Implementing Decision (EU) 2021/914 of 4 June 2021. **“Security Incident”** means a breach of SUBCONTRACTOR’s security or systems leading to the actual or potential accidental or unlawful destruction, loss, alteration, disclosure of, or access to, Customer Data. **“Services”** are as defined in the Agreement. **“Standard Contractual Clauses**” or **“SCCs**” means, (a) in respect of transfers of Personal Data from the EEA, (i) the Controller-to-Processor Clauses, or (ii) the Processor to-Processor Clauses; (b) in respect of transfers of Personal Data from the UK, the “International Data Transfer Addendum to the EU Commission Standard Contractual Clauses, Version B1.0, in force 21 March 2022” to the SCCs, with Customer as data exporter and SUBCONTRACTOR as data importer, or any equivalent clauses issued by the relevant competent authority of the UK, and (c) in respect of transfers of Personal Data from Switzerland or any other country, whether or not in Europe, the clauses are as required by law and agreed to between the parties; in each case as amended and replaced from time to time; each as applicable in accordance with Sections 12.2.1 and 12.2.2. “**Subcontractor Network**” means SUBCONTRACTOR’s facilities, servers, networking equipment, and software systems (for example, virtual firewalls) that are within SUBCONTRACTOR’s control and are used to provide the Services. SUBCONTRACTOR as used in this definition will include SUBCONTRACTOR’s suppliers or Subprocessors. “**Subcontractor Security Standards**” means the security standards attached to and incorporated into this DPA as Annex I (Physical Security) and Annex II (Technical and Organisational Security Measures). “**Subprocessor**” means means any entity, agent or contractor engaged by SUBCONTRACTOR who may process Customer Data on behalf of SUBCONTRACTOR, provide principal services, or is identified in Annex III as attached to and incorporated into this DPA. **“Third Country”** means a country outside the EEA not recognised by the European Commission as providing an adequate level of protection for personal data (as described in the GDPR or another jurisdiction with similar legal or regulatory framework), and excluding countries approved as providing adequate protection for Personal Data by the European Commission from time to time to the extent Subcontractor has complied with the applicable adequacy ruling obligations. **“UK”** means the United Kingdom. _Last Updated July 26, 2023_ **Annex I** **SUBCONTRACTOR Physical Security** Capitalized terms not otherwise defined in this annex have the meanings assigned to them in the Agreement. **1. Physical Access Controls.** To the degress that physical components of the Subcontractor Network are housed in facilities (the “**Facilities**”), physical barrier controls will be used to prevent unauthorised entrance to the Facilities. Passage through the physical barriers at the Facilities will require either electronic access control validation (for example, card access systems, etc.) and/or validation by human security personnel (for example, contract or in-house security guard service, receptionist, etc.). Employees and certain contractors will be assigned photo-ID badges to be worn while employees and contractors are at the Facilities. Visitors and any other contractors will sign-in with designated personnel, show appropriate identification, be assigned a visitor ID badge that must be worn while the visitor or contractor is at any of the Facilities, and be continually escorted by authorised employees or contractors while visiting the Facilities. **2. Physical Security Protections.** All access points (other than main entry doors) are maintained in a secured (locked) state. Access points to the Facilities are monitored by video surveillance cameras designed to record all individuals accessing the Facilities. SUBCONTRACTOR also maintains electronic intrusion detection systems designed to detect unauthorised access to the Facilities, including monitoring points of vulnerability (for example, primary entry doors, emergency egress doors, roof hatches, dock bay doors, etc.) with door contacts, glass breakage devices, interior motion-detection, or other devices designed to detect individuals attempting to gain access to the Facilities. All physical access to the Facilities by employees and contractors is logged and routinely audited. **ANNEX II** **TECHNICAL AND ORGANISATIONAL SECURITY MEASURES** **1. SUBCONTRACTOR** will implement, maintain and enforce appropriate internal security policies and procedures, and procures that its Subprocessors do likewise, which are designed to: a. secure any Personal Data processed by SUBCONTRACTOR against accidental or unlawful loss, access or disclosure; b. identify reasonably foreseeable and internal risks to security and unauthorised access to the Personal Data processed by SUBCONTRACTOR; c. minimise security risks, including through risk assessment and regular testing; d. designate one or more employees to coordinate and be accountable for the internal security policies and procedures, and, taking into account the global distribution of SUBCONTRACTOR staff, such internal security policies and procedures will manage the access allowed to the Subcontractor Network from each network connection and user, including the use of firewalls or functionally equivalent technology and authentication controls; and e. meet or exceed the following additional measures: - A SOC2 Type II annually; - Encryption At-Rest; - Encryption In-Transit; - Password Requirements; - Key Management; - Risk Assessment; - Vendor Risk Management; - User Provisioning/Deprovisioning; - Subcontractor Network Security; - Vulnerability Management; - Incident Management; - Change Management; - System Logging/Monitoring; - Data Management; - Communication; - Business Continuity; and - Disaster Recovery. **2. SUBCONTRACTOR** will, and will use reasonable efforts to procure that its Subprocessors, conduct periodic reviews of the security of their network and the adequacy of their information security program as measured against industry security standards and its policies and procedures. **3. SUBCONTRACTOR** will, and will use reasonable efforts to procure that its Subprocessors, periodically evaluate the security of their network and associated services to determine whether additional or different security measures are required to respond to new security risks or findings generated by the periodic reviews. --- --- title: "University Participation & Consent Form" url: "https://www.getdbt.com/university-consent-form" --- # University Participation & Consent Form University Partners Program --- --- title: "University Partners Program Terms" url: "https://www.getdbt.com/university-partners-program-terms" --- # University Partners Program Terms Program Agreement *** Please read through these dbt Labs University Partners Program Terms (the “**Agreement**”) between dbt Labs, Inc. (“**dbt Labs**”) and you (whether (a) an Educational Institution, or (b) a Qualified Member of an Educational Institution, each referred to as the “**University Partner**”, “**You**”, or “**Your**”). In order to join dbt Labs’ University Partners program (the “**Program**”), You will need to accept this Agreement. If You are entering into this Agreement on behalf of an Educational Institution, You represent that You have the legal authority to do so. If You are entering into this Agreement as a Qualified Member, You agree that Your use of the Educational Offerings (defined below) shall be limited to personal instructional use, for the Acceptable Purpose (defined below), in Your individual capacity and not on behalf of any Educational Institution. You warrant that Your acceptance of this Agreement in connection with the Program is in Your personal capacity and does not represent or authorize any dbt Labs commitments or obligations to or from any Educational Institution. We will use any information that You provide to us in connection with the Program in accordance with dbt Labs’ [Privacy Policy](https://www.getdbt.com/cloud/privacy-policy). This Agreement is effective as of the date of University Partner’s countersignature or electronic acceptance (the “**Effective Date**”). dbt Labs and University Partner are each a **“Party**” and collectively the “**Parties**” under this Agreement. ## 1. Program Overview & Eligibility 1.1 PROGRAM OVERVIEW. This Agreement governs Your participation in the Program and Your use of dbt Labs’ resources, products, and services, including but not limited to, the Software, dbt Learn, Documentation, Program Materials, and any other products or services provided by dbt Labs to University Partner and/or Participating Students through the Program (collectively, the “**Educational Offerings**”). 1.2 PROGRAM DESCRIPTION. dbt Labs operates the Program to introduce Participating Students to modern analytics engineering practices through guided, hands-on educational experiences and supervised access to the Educational Offerings. The Program is designed to provide Participating Students with exposure to industry-standard tools and workflows and may include co-facilitated instructional sessions, hackathon-style workshops, self-paced learning pathways, pre- and post-program surveys, enablement activities for University Partner staff, and other educational programming as determined by dbt Labs in its discretion. The specific scope, format, and schedule of Program activities for each University Partner will be coordinated between the Parties’ respective designated contacts. 1.3 PROGRAM ELIGIBILITY. The Program is open to (a) Educational Institutions, and (b) Qualified Members of Educational Institutions, in each case who have been accepted by dbt Labs. dbt Labs reserves the right to accept, remove, or decline any applicant or University Partner from the Program at any time, for any reason or no reason, at its sole discretion. 1.4 EDUCATIONAL NATURE OF PROGRAM. The Parties acknowledge and agree that the Program is an educational enablement initiative only. The Program does not and shall not constitute: (i) an academic partnership, joint venture, or agency relationship; (ii) sponsored research or a joint research collaboration; (iii) an accredited curriculum, academic credit-bearing course, or degree-granting arrangement; (iv) a certification, professional training, or employment guarantee; or (v) an internship, apprenticeship, or work-study program. Neither Party shall have any right, power, or authority to create any obligation or responsibility, express or implied, on behalf of or in the name of the other Party. University Partner retains sole authority over and responsibility for all academic instruction, grading, student evaluation, curriculum decisions, accreditation, and institutional supervision of Participating Students. 1.5 PILOT NATURE AND PROGRAM MODIFICATIONS. The Program is a pilot initiative. dbt Labs reserves the right to modify, enhance, restructure, suspend, or discontinue the Program or any component of the Educational Offerings at its discretion, upon reasonable prior notice to University Partner where practicable. dbt Labs shall have no liability to University Partner or any Participating Student arising from any such modification, suspension, or discontinuation. 1.6 NO AUTHORITY TO BIND. Neither University Partner nor any Participating Student shall have authority to bind dbt Labs, make representations on behalf of dbt Labs, or hold themselves out as agents, representatives, employees, or contractors of dbt Labs. Participating Students may voluntarily share their experiences with the Program or dbt Labs’ Educational Offerings in academic or professional contexts; however, in doing so, Participating Students act independently and entirely on their own behalf. [↑ Back to top](#program-overview--eligibility) ## 2. Responsibilities of the Parties 2.1 DBT LABS RESPONSIBILITIES. dbt Labs shall make the Educational Offerings reasonably available to University Partner and Participating Students for Program participation. dbt Labs may provide enablement support and training resources to designated University Partner personnel who will facilitate or support Program activities. dbt Labs may co-facilitate instructional sessions, workshops, or hackathon-style events in coordination with University Partner. dbt Labs may administer pre- and post-Program surveys, evaluations, or other instruments designed to assess Program effectiveness and learning outcomes. dbt Labs retains sole discretion over the format, substance, timing, and delivery method of the Educational Offerings and all other aspects of the Program. 2.2 UNIVERSITY PARTNER RESPONSIBILITIES. University Partner shall: (i) identify and recruit eligible Participating Students in accordance with Section 4.1; (ii) designate a primary institutional point of contact for coordination with dbt Labs; (iii) provide suitable physical facilities, technology infrastructure, and videoconferencing capabilities necessary for Program activities, at University’s sole expense; (iv) promote the Program through appropriate institutional channels to eligible students; (v) support the onboarding of Participating Students to the Educational Offerings and encourage completion of Program activities; (vi) provide reasonable cooperation in Program delivery, scheduling, and logistics; and (vii) share feedback on Program effectiveness and student outcome data as reasonably requested by dbt Labs. 2.3 NO STUDENT SUPERVISION BY DBT LABS. University Partner acknowledges and agrees that dbt Labs does not supervise, manage, instruct, evaluate, grade, or assume any duty of care with respect to Participating Students. dbt Labs is not responsible for student conduct, physical safety, mental health, accessibility accommodations, or compliance with University Partner’s institutional policies, codes of conduct, or applicable educational regulations. University Partner shall not represent or imply to any Participating Student, faculty member, or third party that dbt Labs bears any such responsibility. 2.4 NO SUPPORT. The Educational Offerings shall be provided without support and dbt Labs shall have no obligation to render any technical support, maintenance, or error correction services in connection with the Program. [↑ Back to top](#program-overview--eligibility) ## 3. Acceptable Purpose 3.1 SCOPE OF GRANT. Subject to the terms of this Agreement and the Program, dbt Labs grants University Partner a non-exclusive, limited, revocable, worldwide, non-sublicensable and non-transferable right for University Partner to use the Educational Offerings solely for: (a) Instructional Use, and/or (b) Non-Commercial Academic Research (the “**Acceptable Purpose**”). 3.2 UNIVERSITY PARTNER RESTRICTIONS. University Partner shall only be entitled to participate in the Program provided that it (1) uses the Educational Offerings only for the Acceptable Purpose, and (2) either (a) remains an accredited Educational Institution, or (b) if University Partner is a Qualified Member, remains affiliated with an accredited Educational Institution. If at any time, at dbt Labs’s sole discretion, University Partner no longer meets the requirements to participate in the Program, or violates this Agreement, dbt Labs shall provide thirty (30) days written notice to University Partner of its finding(s), and this Agreement and University Partner’s ability to participate in the Program shall terminate. 3.3 ADDITIONAL RESTRICTIONS ON USE. In accessing and using the Educational Offerings, University Partner agrees not to (and not to authorize any third party to): (a) use the Educational Offerings except for the Acceptable Purpose; (b) modify or create any derivative works of the Educational Offerings; (c) take any action that would subject the Educational Offerings to any third party terms; (d) copy, distribute, sell, sublicense, rent or lease the Educational Offerings, including any access key provided by dbt Labs, or use such items for hosting, service provider or similar purposes; (e) access the Educational Offerings for competitive analysis or disseminate performance information (including uptime, response time and/or benchmarks) relating to the Software; or (f) violate the terms of this Agreement or the Program. 3.4 EFFECTS OF VIOLATION. If University Partner and/or Participating Student use the Educational Offerings for any purpose other than the Acceptable Purpose, University Partner and/or Participating Student may have their access to the Educational Offerings and/or Program revoked immediately at dbt Labs’ sole discretion. 3.5 COMMUNITY SOFTWARE. Portions of the Educational Offerings are governed by underlying open source licenses as described at [https://docs.getdbt.com/community/resources/oss-sa-projects](https://docs.getdbt.com/community/resources/oss-sa-projects), including but not limited to the Community Software. This Agreement establishes the rights and obligations associated with the Educational Offerings pursuant to the Program and is not intended to limit University Partner’s right to software code under the terms of an open-source license. [↑ Back to top](#program-overview--eligibility) ## 4. Participating Students 4.1 RESPONSIBILITY FOR PARTICIPATING STUDENTS. University Partner acknowledges and agrees that it is solely responsible for all aspects of Participating Students’ involvement in the Program. University Partner shall ensure that each Participating Student: (i) is validly enrolled at or formally affiliated with University Partner at the time of participation; (ii) satisfies all applicable age and legal eligibility requirements, including minimum age requirements under applicable law and the Terms of Use; (iii) participates voluntarily and not under academic compulsion; (iv) complies with all applicable laws, regulations, institutional policies, the Terms of Use, and the terms of this Agreement; and (v) accesses and uses the Educational Offerings solely for the Acceptable Purpose authorized under this Agreement. University Partner shall not knowingly permit participation by any individual who does not satisfy the foregoing requirements. 4.2 CONSENTS AND PERMISSIONS. University Partner shall obtain, and shall maintain throughout the duration of each Participating Student’s involvement in the Program, all permissions, disclosures, authorizations, and consents required under applicable law, regulation, or institutional policy for Participating Students to: (a) participate in Program activities; (b) create individual accounts on the Educational Offerings; (c) participate in sessions that may be recorded by dbt Labs; (d) complete surveys, evaluations, or other feedback instruments; and (e) have their participation data and Program outcomes collected and used as described in this Agreement. Where a Participating Student is a minor under applicable law, University Partner is responsible for obtaining all required parental or guardian consent. dbt Labs shall have no obligation or responsibility to obtain any such consents or permissions. 4.3 RESPONSIBILITY FOR STUDENT CONDUCT. For purposes of this Agreement, any acts or omissions of Participating Students in connection with the Program or the Educational Offerings shall be deemed acts or omissions of University Partner. University Partner assumes full responsibility for the conduct of Participating Students as if such conduct were that of University Partner itself, and University Partner’s obligations under this Agreement, including its indemnification obligations under Section 11.3, extend to and encompass the actions and omissions of Participating Students. 4.4 ENFORCEMENT RIGHTS. dbt Labs reserves the right, in its sole discretion, to suspend, restrict, or terminate any Participating Student’s access to the Educational Offerings at any time and for any reason, including violation of the Terms of Use, this Agreement, or any applicable law, without prior notice to University Partner and without terminating or otherwise affecting this Agreement. dbt Labs shall use reasonable efforts to notify University Partner promptly following any such action. [↑ Back to top](#program-overview--eligibility) ## 5. Compensation Participation in the Program is provided without monetary consideration by either Party. Neither Party shall be obligated to pay any fees, expenses, or other amounts to the other Party in connection with this Agreement. dbt Labs may, at its sole discretion, provide non-monetary benefits to University Partner or Participating Students in connection with the Program, including educational resources, platform access, promotional items, workshops, and networking and internship opportunities (collectively, “**Program Benefits**”). Such Program Benefits shall have no cash or monetary value, shall not constitute consideration for purposes of this Agreement, and may be modified or discontinued at any time. For the avoidance of doubt, nothing in this Agreement entitles University Partner or any Participating Student to free or discounted access to dbt Labs’ paid subscriptions, professional services, or other commercial offerings. Any such offerings are subject to dbt Labs’ separate commercial terms and pricing. [↑ Back to top](#program-overview--eligibility) ## 6. Feedback, Program Data & Recordings. 6.1 PURPOSE. University Partner acknowledges that the evaluation, measurement, and continuous improvement of the Educational Offerings and dbt Labs’ educational initiatives are core purposes of the Program. The collection and analysis of Program Data and Feedback are integral to dbt Labs’ ability to operate, assess, and enhance the Program and the Educational Offerings. 6.2 COLLECTION AND USE OF PROGRAM DATA. dbt Labs may collect, store, process, and analyze Program Data in connection with: (a) operating, administering, and delivering the Program; (b) evaluating Program effectiveness and learning outcomes; (c) improving, enhancing, and developing the Educational Offerings, and other dbt Labs products and services; (d) conducting internal research and analytics; and (e) preparing reports, impact statements, and marketing materials describing Program outcomes and trends. University hereby consents to such collection and use on its own behalf (to the extent such consent can be provided under applicable law), and University shall cooperate in acquiring any such necessary consents for collection and use from Participating Students. University shall also cooperate in providing access to Program Data (as such consents permit and as reasonably requested by dbt Labs). Program Data is dbt Labs’ CI. 6.3 RECORDINGS. University Partner acknowledges and agrees that dbt Labs may record Program sessions, workshops, and related activities for purposes including training, quality assurance, program improvement, and internal reference. University Partner is solely responsible for obtaining all institutional permissions and Participating Student consents required under applicable law or institutional policy for such recordings, as set forth in Section 4.2. 6.4 FEEDBACK. University Partner and Participating Students may provide Feedback to dbt Labs. To the extent University Partner or any Participating Student provides Feedback, dbt Labs shall have a royalty-free, worldwide, irrevocable, perpetual license to use, reproduce, modify, create derivative works from, distribute, and otherwise exploit such Feedback for any purpose, including incorporating the Feedback into the Educational Offerings or using it to develop and improve the Educational Offerings and other dbt Labs products or services, without attribution or compensation. Any Feedback provided by University Partner or any Participating Student may be used by dbt Labs in its sole discretion, including to develop, improve, and market the Educational Offerings and other products and services, without restriction, obligation, attribution, or compensation. Feedback shall not be considered CI of University Partner or any Participating Student, regardless of any designation to the contrary. 6.5 NO RESEARCH COLLABORATION. The Parties acknowledge and agree that participation in the Program does not constitute academic research, sponsored research, a joint research collaboration, or any other arrangement subject to institutional review board oversight or academic research governance. Program Data and Feedback are not jointly owned research output and shall not be subject to academic publication rights or institutional research ownership policies unless separately agreed in writing by the Parties. [↑ Back to top](#program-overview--eligibility) ## 7. Ownership & Intellectual Property Rights 7.1 OWNERSHIP OF EDUCATIONAL OFFERINGS. dbt Labs shall retain all right, title, and interest, including all Intellectual Property Rights, in and to the Educational Offerings, and all related technology, software, content, methodologies, processes, workflows, know-how, trade secrets, and derivative works, including all improvements, modifications, enhancements, and updates thereto, whether or not developed in connection with the Program. Except for the limited rights expressly granted in this Agreement, no license or right of any kind is granted to University Partner, any Participating Student, or any third party by implication, estoppel, exhaustion, or otherwise. 7.2 UNIVERSITY PARTNER CONTENT. University Partner retains all right, title, and interest in materials independently developed by University without use of or reference to dbt Labs Confidential Information, the Educational Offerings, or Program Data (“**University Partner Content**”). University Partner hereby grants to dbt Labs a non-exclusive, royalty-free, worldwide license to use, reproduce, and display University Partner’s name, trademarks, logos, and University Partner Content solely as reasonably necessary to administer, promote, and publicize the Program, subject to Section 8 (Publicity) and any brand guidelines provided by University Partner. 7.3 STUDENT WORK PRODUCT. Participating Students retain ownership of original, independently authored project work and outputs unique to the Participating Student they create during the Program without use of or reference to dbt Labs Confidential Information, the Educational Offerings, or Program Data (“**Participating Student Work Product**”). Notwithstanding the foregoing, the Parties acknowledge that: (a) the underlying Educational Offerings, software, templates, data models, methodologies, workflows, and technology embedded in or used to create any such Participating Student Work Product remain the exclusive intellectual property of dbt Labs and its licensors; and (b) dbt Labs may freely use, reference, and reproduce generalized learnings, techniques, anonymized examples, aggregated themes, and insights derived from Program activities for educational, product improvement, research, or marketing purposes. 7.4 NO JOINT DEVELOPMENT OR OWNERSHIP. The Parties agree that participation in the Program does not create any joint intellectual property, joint authorship, co-ownership, or co-development rights. No intellectual property ownership is transferred under this Agreement except as expressly stated herein. University Partner shall not acquire any right, title, or interest in the Educational Offerings by reason of this Agreement, Program participation, or the provision of Feedback. All courseware, instructional sequences, pedagogical approaches, and training methodologies developed or used by dbt Labs in connection with the Program are and remain the sole property of dbt Labs. 7.5 RESERVATION OF RIGHTS. All rights in the Educational Offerings not expressly granted under this Agreement are reserved by dbt Labs and its licensors. No implied licenses are granted under this Agreement. [↑ Back to top](#program-overview--eligibility) ## 8. Publicity 8.1 PERMITTED REFERENCES. Each Party may publicly reference its participation in the Program, including through institutional websites, press releases, social media posts, blog entries, and marketing or promotional materials, provided that: (a) such references accurately represent the nature and scope of the Program and do not overstate or mischaracterize the relationship between the Parties; (b) use of the other Party’s name, logo, or trademarks complies with applicable brand guidelines and is approved in writing (including by email) prior to first use; and (c) no statement implies endorsement, sponsorship, affiliation, or certification beyond participation in the Program. 8.2 DBT LABS BRAND GUIDELINES. Any use by University Partner of dbt Labs’ logo, name or other marks shall be in accordance with dbt Labs brand guidelines available at [https://www.getdbt.com/brand-guidelines/](https://www.getdbt.com/brand-guidelines/). 8.3 REVOCATION. Either Party may revoke permission to use its name, logos, or trademarks at any time upon reasonable written notice. Upon receipt of such notice, the other Party shall cease all use of such marks in new materials within thirty (30) days and shall use commercially reasonable efforts to remove or update existing materials within a reasonable period. [↑ Back to top](#program-overview--eligibility) ## 9. Confidentiality 9.1 DEFINITION. “**CI**” means the terms of this Agreement and any non-public information, whether provided orally or in writing, either designated in writing as “Confidential” or “Proprietary” or that a Party would reasonably understand is confidential, and includes information related to technology, techniques, ideas, concepts, algorithms, source code, methodologies, workflows, implementation processes, current and future products and services, research, engineering, designs, financials, processes, customer lists, forecasts, roadmaps, marketing plans, pricing, discounts and proposals. CI will not include any information that: (a) is or becomes generally available to the public through no fault of or breach of this Agreement by receiving Party; (b) was rightfully in receiving Party’s possession when disclosed without receiving Party’s obligation of confidentiality; (c) is independently developed by receiving Party without use of disclosing Party’s CI; (d) is rightfully obtained by receiving Party from a third party under no duty of confidentiality to disclosing Party; or (e) receiving Party is permitted to publicly disclose under this Agreement. All CI disclosed under this Agreement is the property of the disclosing Party. 9.2 RESTRICTIONS. Neither Party will disclose the other Party’s CI to any third party or use the other Party’s CI for any purpose, except as necessary to fulfill its obligations or exercise its rights under this Agreement. Each Party will use at least the same degree of care (and no less than reasonable care) to prevent unauthorized access, use, or dissemination of the other party’s CI as it uses to protect its own CI. Receiving Party may disclose the disclosing Party’s CI pursuant to a valid court order or subpoena, to the extent receiving Party: (a) unless prohibited by law, provides notice sufficient to permit disclosing Party an opportunity to pursue protective measures; (b) provides reasonable assistance with such efforts; and (c) discloses only the minimum legally required to be disclosed. 9.3 RETURN OF CI. Confidentiality obligations expire three (3) years after disclosure. Receiving Party will, upon written request of disclosing Party, use commercially reasonable efforts to delete, destroy or render CI inaccessible. 9.4 REMEDIES. The Parties agree that receiving Party’s actual or proposed disclosure of CI, except as expressly permitted by dbt Labs, will result in irreparable harm and disclosing Party may seek an injunction. [↑ Back to top](#program-overview--eligibility) ## 10. Term & Termination 10.1 TERM. The initial term of this Agreement shall commence on the Effective Date and shall expire one (1) year later (the “**Initial Term**”). This Agreement may renew for successive one (1) year periods upon dbt Labs confirming reacceptance of University Partner into the Partners Program (each a “**Renewal Term**”), unless terminated as described below. The Initial Term and any Renewal Terms shall be the “**Term**”. 10.2 TERMINATION. Following the Initial Term, either Party may terminate this Agreement upon sixty (60) days’ prior written notice to the other Party. Either Party may immediately terminate this Agreement upon written notice if the other Party breaches its obligations under this Agreement and fails to cure such breach within thirty (30) days following receipt of notice from the non-breaching Party. A Party that provides notice of breach must include in the notice a description of the alleged breach in reasonable detail. In addition, either Party may immediately terminate this Agreement upon written notice to the other Party in the event that the other Party becomes the subject of a petition in bankruptcy or any proceeding related to its insolvency or any assignment for the benefit of creditors. 10.3 SUSPENSION. dbt Labs may also suspend University Partner’s use of the Educational Offerings or terminate this Agreement immediately if dbt Labs is: (a) required to do so by law; (b) if University Partner (i) is an Educational Institution and no longer qualifies as an accredited Educational Institution, or (ii) is a Qualified Member and is no longer affiliated with an Educational Institution; or (c) if dbt Labs determines that continuing under this Agreement could result in legal or business liability or cause harm to its products, services, reputation, or users. 10.4 EFFECT OF TERMINATION. Upon any termination of this Agreement, University Partner’s rights to use the Educational Offerings (including related access keys and credentials) will immediately terminate and University Partner will cease all such use, but any provisions of this Agreement that by their nature should survive termination or expiration, including without limitation provisions relating to intellectual property ownership, confidentiality, disclaimers, limitations of liability, indemnification, and general provisions governing interpretation and enforcement, shall survive any termination or expiration of this Agreement. dbt Labs will have no obligation or liability resulting from termination or suspension of this Agreement, as permitted herein. [↑ Back to top](#program-overview--eligibility) ## 11. Warranty & Indemnification 11.1 WARRANTY. Both Parties hereby represent and warrant that they are legally entitled to enter into this Agreement. University Partner further represents and warrants that: (a) either (i) it is an accredited Educational Institution duly organized and in good standing under the laws of its jurisdiction, or (ii) if University Partner is a Qualified Member, such individual is currently affiliated with an accredited Educational Institution in good standing; (b) University Partner has all necessary authority and approval to enter into this Agreement and to participate in the Program; (c) it will comply, and will ensure compliance by Participating Students, with all applicable laws, regulations, and institutional policies in connection with the Program; (d) it has obtained or will obtain all consents, authorizations, and permissions required under applicable law and institutional policy prior to any Participating Student’s first access to the Educational Offerings; and (e) all information provided to dbt Labs in connection with the Program is and shall remain accurate and complete in all material respects. 11.2 DISCLAIMER. EXCEPT AS EXPRESSLY STATED HEREIN, ANYTHING PROVIDED IN CONNECTION WITH THIS AGREEMENT IS PROVIDED “AS-IS”, WITHOUT ANY WARRANTIES OF ANY KIND. EACH PARTY DISCLAIMS ANY IMPLIED WARRANTIES, INCLUDING, WITHOUT LIMITATION, ANY IMPLIED WARRANTIES OF MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE. 11.3 UNIVERSITY PARTNER INDEMNIFICATION. University Partner shall defend, indemnify, and hold harmless dbt Labs and its Affiliates, and their respective officers, directors, employees, agents, successors, and assigns (collectively, the "**dbt Labs Indemnitees**") from and against any and all third-party claims, actions, proceedings, suits, demands, damages, liabilities, losses, judgments, settlements, costs, and expenses (including reasonable attorneys’ fees and costs of investigation) arising out of or relating to: (i) the acts, omissions, negligence, or willful misconduct of University Partner in connection with the Program; (ii) University Partner’s failure to obtain or maintain any required permissions, disclosures, authorizations, or consents, including parental consent; (iii) any violation of applicable law, regulation, or institutional policy by University Partner in connection with the Program; (iv) any unauthorized or improper access to or use of the Educational Offerings by University Partner if (i) an Educational Institution, University Partner personnel or (ii) a Qualified Member, University Partner itself; (v) any breach of this Agreement by University Partner; or (vi) if University Partner is an Educational Institution, any personal injury, property damage, or other harm occurring at Program events hosted at University Partner’s facilities. As a condition to University’s indemnification obligations hereunder: (a) dbt Labs shall promptly provide University Partner with written notice of any claim for which indemnification is sought, provided that any delay in providing such notice shall not relieve University Partner of its indemnification obligations except to the extent University Partner is materially prejudiced by such delay; (b) University Partner shall have sole control of the defense and settlement of any such claim, provided that University Partner shall not settle any claim in a manner that admits fault or liability on behalf of any dbt Labs Indemnitee, or imposes any obligation on any dbt Labs Indemnitee, without dbt Labs’ prior written consent; and (c) dbt Labs shall provide reasonable cooperation in the defense of any such claim at University Partner’s expense. [↑ Back to top](#program-overview--eligibility) ## 12. Limitations of Liability 12.1 WAIVER OF CERTAIN DAMAGES. TO THE MAXIMUM EXTENT PERMITTED BY LAW, IN NO EVENT SHALL EITHER PARTY BE LIABLE TO THE OTHER FOR LOST PROFITS OR REVENUE OR LOSS OF USE OR DATA, COSTS OF COVER OR SUBSTITUTE GOODS OR SERVICES, OR FOR INCIDENTAL, CONSEQUENTIAL, PUNITIVE, SPECIAL OR EXEMPLARY DAMAGES, OR INDIRECT DAMAGES OF ANY TYPE OR KIND, HOWEVER CAUSED, RELATED TO OR ARISING OUT OF THIS AGREEMENT OR THE RIGHTS, LICENSES, PRODUCTS OR SERVICES PROVIDED UNDER THIS AGREEMENT, WHETHER BY BREACH OF WARRANTY, BREACH OF CONTRACT, NEGLIGENCE, TORT, OR ANY OTHER LEGAL THEORY, AND WHETHER OR NOT THE PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGES. 12.2 LIABILITY CAP. TO THE MAXIMUM EXTENT PERMITTED BY LAW, EXCEPT FOR: (A) UNIVERSITY PARTNER’S INDEMNIFICATION OBLIGATIONS UNDER SECTION 11; (B) EITHER PARTY’S BREACH OF ITS CONFIDENTIALITY OBLIGATIONS; (C) UNIVERSITY PARTNER’S BREACH OF THE LICENSE RESTRICTIONS; OR (D) EITHER PARTY’S GROSS NEGLIGENCE, FRAUD, OR WILLFUL MISCONDUCT, THE TOTAL, CUMULATIVE LIABILITY OF EACH PARTY ARISING OUT OF OR RELATED TO THIS AGREEMENT OR THE RIGHTS, LICENSES, PRODUCTS OR SERVICES PROVIDED UNDER THIS AGREEMENT, WHETHER BASED ON CONTRACT, TORT (INCLUDING NEGLIGENCE), OR ANY OTHER LEGAL THEORY, SHALL BE LIMITED TO FIVE HUNDRED U.S. DOLLARS ($500.00). 12.3 ALLOCATION OF RISK. THE LIMITATIONS AND EXCLUSIONS OF LIABILITY SET FORTH IN THIS SECTION 12 APPLY REGARDLESS OF WHETHER THE DAMAGES ARE BASED ON WARRANTY, CONTRACT, TORT, STRICT LIABILITY, OR ANY OTHER LEGAL THEORY, AND SHALL APPLY EVEN IF A PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGES. THE PARTIES ACKNOWLEDGE THAT THE LIMITATIONS SET FORTH IN THIS SECTION REFLECT THE ALLOCATION OF RISK BETWEEN THE PARTIES AND FORM AN ESSENTIAL BASIS OF THE BARGAIN BETWEEN THEM. THE EDUCATIONAL OFFERINGS AND PROGRAM WOULD NOT BE PROVIDED WITHOUT SUCH LIMITATIONS. [↑ Back to top](#program-overview--eligibility) ## 13. Export Controls The Educational Offerings are subject to export restrictions by the United States government and import restrictions by certain foreign governments. University Partner agrees to comply with all applicable export and import laws and regulations in its use of the Educational Offerings. University Partner shall not (and shall not allow any third-party to) remove or export from the United States or allow the export or re-export of any part of the Educational Offerings: (a) into (or to a national or resident of) any embargoed or terrorist-supporting country; (b) to anyone on the U.S. Commerce Department’s Table of Denial Orders or U.S. Treasury Department’s list of Specially Designated Nationals; (c) to any country to which such export or re-export is restricted or prohibited, or as to which the United States government or any agency thereof requires an export license or other governmental approval at the time of export or re-export without first obtaining such license or approval; or (d) otherwise in violation of any export or import restrictions, laws or regulations of any United States or foreign agency or authority. University Partner represents and warrants that it is not located in, under the control of, or a national or resident of any such prohibited country or on any such prohibited party list. [↑ Back to top](#program-overview--eligibility) ## 14. Security & Data Protection 14.1 DBT LABS RESPONSIBILITIES. With respect to University Partner’s use of the Educational Offerings, dbt Labs shall be responsible for establishing and maintaining a commercially reasonable information security program that is designed to: (i) ensure the security and confidentiality of the University Partner Content; (ii) protect against any anticipated threats or hazards to the security or integrity of the University Partner Content; (iii) protect against unauthorized access to, or use of, the University Partner Content; and (iv) ensure that all subcontractors of dbt Labs, if any, comply with all of the foregoing. In no case shall the safeguards of dbt Labs’s information security program be less stringent than the information security safeguards used by dbt Labs to protect its own commercially sensitive data. University Partner shall use commercially reasonable security and anti-virus measures when accessing and using the Educational Offerings and to prevent unauthorized access to, or use of the Educational Offerings and notify dbt Labs promptly of any such unauthorized access or use of which it becomes aware. 14.2 DATA PROCESSING. To the extent dbt Labs Processes the data of University Partner in a jurisdiction that requires a data processing agreement or similar document, dbt Labs will process such Personal Data in accordance with Data Protection Laws applicable to dbt Labs as Processor of such Personal Data and in accordance with the dbt Labs Data Processing Addendum (“**DPA**”), available at [https://www.getdbt.com/cloud/dpa](https://www.getdbt.com/cloud/dpa), which the Parties agree is effective between the Parties as of the date hereof and is supplemental, applicable to, and incorporated into the Agreement. Capitalized terms in this subsection not otherwise defined herein have the meanings set forth in the DPA. 14.3 UNIVERSITY PARTNER OBLIGATIONS. University Partner shall also maintain and handle all University Partner Content with reasonably adequate privacy and security measures and in compliance with all applicable privacy laws and regulations. [↑ Back to top](#program-overview--eligibility) ## 15. Terms of Use & Platform Governance 15.1 INCORPORATION OF TERMS OF USE. Access to and use of the Educational Offerings is governed by the Terms of Use, which are hereby incorporated by reference into this Agreement. The Terms of Use constitute a binding agreement between dbt Labs and each individual who accesses or uses the Educational Offerings, including Participating Students and University Partner personnel. University Partner acknowledges that it has reviewed the Terms of Use and understands the obligations and restrictions set forth therein. 15.2 UNIVERSITY PARTNER OBLIGATIONS REGARDING TERMS OF USE.** **University Partner agrees that it shall: (a) inform all Participating Students, prior to their first access, that use of the Educational Offerings is subject to and governed by the Terms of Use; (b) require Participating Students to access the Educational Offerings only through individually authorized accounts; and (c) use reasonable efforts to ensure that Participating Students and University Partner personnel comply with the Terms of Use at all times. Each Participating Student must independently accept the Terms of Use as a condition of creating an account on or accessing the Educational Offerings. dbt Labs may enforce the Terms of Use directly against any Participating Student, including by suspending or terminating such Participating Student’s access. 15.3 CONFLICT.** **In the event of any conflict or inconsistency between this Agreement and the Terms of Use: (i) with respect to access to and use of the Educational Offerings by Participating Students or University Partner personnel, the Terms of Use shall control; and (ii) with respect to the administration of the Program and the relationship between the Parties, this Agreement shall control. [↑ Back to top](#program-overview--eligibility) ## 16. Miscellaneous This Agreement is the sole and entire agreement of the Parties and supersedes all prior and contemporaneous understandings, both written and oral, regarding the subject matter. Parties to this Agreement will first attempt to settle any dispute through good-faith negotiation. If the dispute cannot be settled between the Parties via negotiation, and litigation is necessary, this Agreement will be interpreted based on the laws of the State of Delaware, without regard to the conflict of law provisions of such state. A Party will not be in breach of this Agreement for delays or performance failures caused solely by reasons outside of its reasonable control. dbt Labs may assign rights and obligations under this Agreement to a valid successor-in-interest, and upon any such assignment, dbt Labs will have no further obligation or liability to University Partner. University Partner may not assign its rights and obligations under this Agreement without dbt Labs’ prior written approval. No waiver of or failure to act upon any of the provisions of this Agreement or any right or remedy arising under this Agreement constitute a waiver of any other provisions, rights or remedies (whether similar or dissimilar). Use of “include” (and “includes,” etc.) provides examples not limitations. [↑ Back to top](#program-overview--eligibility) ## 17. Definitions 17.1 “**Affiliate**” means any entity(ies) controlling, controlled by, and/or under common control with a party hereto, where “control” means the ownership of more than 50% of the voting securities in such entity. 17.2 “**Community Software**” means the publicly available, community-developed open-source software and components which may be provided with the Software. 17.3 “**dbt Labs University Partners Program**” or “**Program**” means the dbt Labs program introducing students to modern analytics engineering practices using the Educational Offerings, including workshops, hackathon-style instructional sessions, learning pathways, enablement activities, surveys, and related programming. 17.4 “**dbt Learn**” means the dbt Labs managed online learning management system used to instruct authorized users on the Software. 17.5 "**Documentation**" means dbt Labs’ standard user guides, technical documentation, API references, knowledge-base articles, and instructional materials describing the features, functionality, and use of the Educational Offerings, as updated by dbt Labs from time to time and made available at [https://docs.getdbt.com](https://docs.getdbt.com/) or through the Educational Offerings. 17.6 “**Educational Institution**” means an organization that: (i) has been accredited or officially recognized by an authorized governmental agency within its applicable local, state, provincial, federal or national government; (ii) has the primary purpose of providing structured, formal education and training to its enrolled students or participants; (iii) issues recognized credentials, which may include degrees (such as associate, bachelor’s, or graduate degrees), diplomas, certificates, or similar formal qualifications; and (iv) is a non-profit organization. 17.7 "**Feedback**" means any suggestions, comments, ideas, enhancement requests, recommendations, corrections, or other feedback relating to the Educational Offerings, the Program, the Documentation, or any other dbt Labs’ products or services. 17.8 “**Instructional Use**” means activities directly related to learning, training, or development including academic instruction that are part of the instructional functions of the Educational Institution. 17.9 “**Intellectual Property Rights**” means all intellectual property rights throughout the world, including, without limitation, patents, copyrights, Trademarks, trade secrets and contractual or other rights in confidential information, moral rights, rights of privacy and publicity, and any other intellectual and industrial property and proprietary rights including registrations, applications, renewals and extensions of such rights worldwide. 17.10 “**Non-Commercial Academic Research**” means not-for-profit research projects, which are not intended to, or do not in fact, produce results, works, services, or data for commercial use or the sole benefit of the Educational Institution or any third-party. 17.11 "**Participating Students**" means individuals who are enrolled at, formally affiliated with, or sponsored by University Partner and who participate in the Program or access the Educational Offerings through University Partner in connection with the Program. Participating Students are not parties to this Agreement 17.12 “**Privacy Policy**” means the dbt Labs Privacy Policy located at [https://www.getdbt.com/cloud/privacy-policy](https://www.getdbt.com/cloud/privacy-policy) or any successor site thereto. 17.13 "**Program Data**" means all data, metrics, and information collected, generated, or derived through the operation and evaluation of the Program, including participation and attendance information, platform usage and adoption analytics, survey responses and learning outcome evaluations, session recordings, interaction metrics, and other operational data, as well as analyses, case studies, impact reports, and summaries describing Program outcomes, adoption trends, and educational effectiveness. 17.14 "**Program Materials**" means the educational workshops, exercises, templates, presentations, facilitator guides, enablement kits, and other instructional and learning resources provided by dbt Labs in connection with the Program. 17.15 “**Qualified Member**” means any of the following individuals affiliated with an Educational Institution: (i) student-facing faculty; (ii) non-faculty staff employees; (iii) anyone performing academic, not-for-profit research on behalf of or in collaboration with an Educational Institution; and (iv) currently enrolled students. 17.16 “**Software”** means the dbt Labs hosted software platform (including dbt Cloud and the dbt VS Code extension), applications, features, tools, learning environments, and related services and functionalities made available by dbt Labs to University Partner and Participating Students in connection with the Program, including all updates, enhancements, modifications, and derivative works thereof. 17.17 “**Terms of Use**” means the dbt Labs Terms of Use located at [https://www.getdbt.com/terms-of-use](https://www.getdbt.com/terms-of-service), which shall only be applicable in the event: (i) University Partner wishes to purchase the Software, or (ii) University Partner uses the Software in any manner other than the Acceptable Purpose. 17.18 ** **“**University Partner Content**” is all software, information, content and data provided by or on behalf of University Partner or made available or otherwise distributed through the use of the Educational Offerings. [↑ Back to top](#program-overview--eligibility) *** *The dbt Community* ## Join the largest community shaping the future of data & AI The dbt Community is your gateway to best practices, innovation, and direct collaboration with thousands of data leaders and AI practitioners worldwide. Ask questions, share insights, and grow alongside a welcoming network of builders. [Join the Community](https://www.getdbt.com/community/join-the-community) | [Explore the Community](https://www.getdbt.com/community) --- --- title: "Student Participation & Consent Form" url: "https://www.getdbt.com/university-student-consent-form" --- # Student Participation & Consent Form University Partners Program --- --- title: "dbt Wizard Desktop Waitlist" url: "https://www.getdbt.com/wizard-desktop-waitlist" --- *Now in private beta* ## dbt Wizard Desktop waitlist Run more, worry less, ship with confidence. *** ## Join the Wizard Desktop beta waitlist! A dedicated local workspace for the work that takes time. No platform account required. - **Work in parallel -** Run several complex tasks side by side, no more juggling terminal windows. - **A space of its own -** A dedicated local workspace, changes automatically isolated. - **See it before it ships -** Preview the code, the data, and the lineage before anything goes out. - **You're still in charge - **Guide how Wizard validates its work with a visual workflow. _This is a private beta with limited spots — if you're selected, someone from our team will reach out. _