Anomaly detection
Schema-level monitoring that learns freshness and completeness from history and flags tables that went quiet or arrived thin.
Why it is worth watching
The only layer that catches an upstream job stopping, which no row-level rule can see.
What Public Preview promises
Open to everyone and supported for production use, though it can still change. On by default, and an admin can turn it off.
| Who can use it | Everyone |
|---|---|
| Production use | Yes |
| Support | The support team |
| On by default | Yes, with an opt-out |
The definitions are Databricks' own, on its release types page. The label on this page is the one the feature's documentation states, last checked on 14 Sept 2026.
Where to read more
It is part of something we wrote up: Data profiling and anomaly detection — Unity Catalog's own quality monitoring, with two halves that answer different questions, two metric tables you can query, and a schedule that costs serverless compute.