Data Observability
Freshness, volume, schema, and quality for the tables your pipelines land — backed by Databricks Unity Catalog
Tables monitored
1,284
Passing
94.1%
Stale tables
23
Schema changes (7d)
11
The four pillars
Every monitored table is scored on the same four checks, so one number is comparable across catalogs.
- Freshness— time since the last successful write
- Volume— row count against its own recent baseline
- Schema— added, dropped, or retyped columns
- Quality— null rates and distribution drift on tracked columns
Breaking changes needing review
Monitored tables
Unity Catalog — catalog.schema.table, scanned on the schedule each organization configures
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