Data quality & trust

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

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

Create a centralized hub for managing key business metrics, ensuring consistency and accuracy across the organization

dbt Semantic Layer

Trusted by teams that trust their data quality.

Rocket Money

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

3,000Tests implemented to ensure data quality
0deficiencies in SOX audit after modernizing system
Read Customer Study
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.

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Why teams trust dbt

Trusted globally. Proven at scale.

Proven at scale

60,000+ teams using dbt

dbt powers trusted analytics workflows and data at scale for the world's largest companies

Customer approved

97% customer satisfaction

Rated 4.9/5 on G2 by thousands of data leaders who trust dbt for critical analytics and AI initiatives.

Deep integrations

Built with leading partners

Community-powered

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.

Report

With dbt, data leaders can spearhead a unified approach for working with data that ensures quality and consistency.

Blog

Build your AI initiatives on trustworthy data

Blog

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.