See the impact of every code change on the data.
See the impact of any code change on downstream datasets and BI dashboards
Prevent errors from entering your data pipeline
Move your data quality “to the left” as you stop the data incidents before they begin. See how any code change in the ELT or BI code affects the resulting data, both on the value and metric levels.
“Datafold is the missing piece of the puzzle for data quality assurance. When I first heard about Datafold, all I could think was “Finally!”
Explore dependencies with ease
Assess 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.
"Column-level lineage gives a holistic view of data dependencies and interdependencies. It’s so powerful - with even more insight than table-level lineage - I get really excited about what it can do!"
Data testing as part of the workflow
Integrate data testing into your development workflow with GitHub and GitLab integrations. See the impact of your change right in the pull request. Prevent regressions and streamline pull request reviews.
"Datafold is a game-changer— there is so much value in actually understanding the effect of your pull request.”
Easily test every code change from every data producer
Data engineers, analysts, and scientists can all test their code the same way. Streamline code review processes knowing that every code change has been tested and checked for consistent data quality assurance.
“Datafold gives us full confidence when we ship changes into production, which historically I couldn’t say about PRs.”
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