Query your data—don't question it.
Power your AI and data development with high quality, trusted data.
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
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
Create a centralized hub for managing key business metrics, ensuring consistency and accuracy across the organization
Trusted by teams that trust their data quality.
Putting data quality to the test
Financial systems demand reliability. When cash is on the line, you need to be able to prove your numbers are accurate. Rocket Money uses a rigorous testing scheme build in dbt to ensure data quality
"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."
Amber Oar, Staff Analytics Engineer
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.
Trusted globally. Proven at scale.
60,000+ 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
Dig deeper into data quality & trust with dbt.
See the ways dbt takes your data stack further.
With dbt, data leaders can spearhead a unified approach for working with data that ensures quality and consistency.
Basic data hygiene techniques, such as testing, play a huge role in improving data quality. However, writing a few tests isn't enough.
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.