Prevent bad code deploys with automated testing
 in CI
Understand how your data changes with code updates, enabling you to identify unexpected regressions before deploying to production. Seamlessly integrates with dbt, Airflow, or any git repository.
Deploy code with greater speed and confidence
Automate testing for every code change
Identify the value-level differences between the development and production versions of your data when Datafold runs in your CI/CD process. Proactively identify unexpected data regressions before your stakeholder does.
Get actionable insights on code changes
Understand the effect of any proposed code change on other datasets, BI dashboards, and ML models using Datafold's integrated column-level lineage. Avoid unexpected regressions and silent breakages.
Deploy code with confidence and speed
Standardize and automate testing for all code updates, enabling your data team to work with greater development velocity and assurance.
How our customers are ensuring data quality with speed and confidence
"Datafold helps you find the hidden changes you didn't know you made to your data, helping you if they're unintended or understanding what's causing them."
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"Datafold allows real visibility into data changes before the changes are live, reducing mistakes and enabling our analysts and stakeholders to feel confident in their changes."
"You can see right off the bat whether your data quality is what you were expecting, and reviewers can see it, too. Now we’re at the rate where we’re automating code reviews, or close to it, on 100 pull requests per month. And this is just the start."
Testing that plugs into your stack
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