Databricks

Integrate Datafold with Databricks for seamless data quality

Prevent data quality issues in Databricks with automated CI testing, ML-powered data monitoring, cross-database data reconciliation, and column-level lineage.

01
Automated data migration testing

Validate migrations with speed and confidence

Ensure data accuracy effortlessly during migrations to Databricks. Datafold automatically validates data parity between your legacy warehouse and Databricks, catching discrepancies early to provide confidence in every migration.

02
CI/CD testing for data transformation workflows

Catch issues in transformation code before they reach production

With Datafold’s CI/CD integration for Databricks, test and validate transformation code as you build. Automated quality checks run with each pull request, enabling your team to catch and resolve issues before deployment.

03
Comprehensive data monitoring across Databricks pipelines

Monitor critical data and metrics with real-time alerts

Datafold’s monitoring tools keep your Databricks pipelines in check, with real-time alerts for schema changes, data diffs, and anomalies. Get notified of any issues instantly, so you can quickly address them and ensure data accuracy across Databricks.

Integration

How Datafold integrates with Databricks