DATA QUALITY MANAGER
Data quality on Databricks, without the heavy lifting.
Define, run, and monitor validation rules straight against your Unity Catalog tables, from a browser, with no code to write. Catch problems at every layer of the Medallion architecture, before they reach the dashboards people trust.
How it works
Four steps, all from a browser. Up and running in under an hour, with nothing to install on your own machine and no pipeline to wire up first.
Browse your catalog
Point the app at Unity Catalog and explore your catalogs, schemas, tables, and columns. Pick the table you want to keep an eye on.
Define your expectations
Build a validation suite in a visual editor. 27+ built-in checks: row counts, null checks, value ranges, regex patterns. Nothing to write by hand.
Run the validation
One click triggers a Databricks Job in your own workspace. The checks run where your data already lives, so nothing ever leaves the tenant.
Monitor the results
Pass and fail results land on a dashboard with trends and interactive charts. When a check fails, your team hears about it over Teams or email.
What you get
Four parts, one job: knowing your data is what you think it is, every time it moves through Databricks.
Visual expectation editor
Build and tweak validation suites in the browser. 27+ expectation types covering row counts, nulls, ranges, and regex. Hand it to a business user, not just an engineer.
Results dashboard
Pass and fail trends over time, interactive charts, and a clear read on which tables are healthy. See quality slipping before anyone downstream does.
Unity Catalog browser
Walk your catalogs, schemas, tables, and columns from inside the app. Find the data you need to validate without leaving the tool.
Failure notifications
When a check fails, the right people hear about it over Microsoft Teams or email. No silent data rot, no surprises in the Monday report.
Secure by design.
The app installs into your Databricks workspace and runs there. Your data is validated where it already lives. We don't copy it, move it, or see it.
Authentication runs through OAuth and respects the Unity Catalog permissions you already have in place. Results are written back as Delta tables you own.
Why we built it
Every data project eventually hits the same wall: nobody trusts the numbers. A dashboard says one thing, a report says another, and the meeting stalls while someone goes off to check the source.
The fix is rarely a bigger tool. Most teams on Databricks don't need a heavyweight governance suite with a six-month rollout. They need a fast way to write down what good looks like for a table, run that check on every load, and get told the moment something breaks.
So we built exactly that, and nothing more. Point it at a table, set your expectations, let it run alongside your jobs. It does what it says it does. No more, no less.
“Data quality isn't a one-time project. It's a continuous practice, applied at every layer, every time data moves.”
Put it to work on your own tables.
Point it at a Unity Catalog table, set your expectations, and see your first validation results inside the hour.
Visit Data Quality Manager