Extract Databricks dashboard lineage
Databricks AI/BI dashboard support is in private preview and is enabled per tenant. The Import AI/BI Dashboards and Enable Dashboard Lineage options stay hidden in the workflow setup until the feature is enabled for your tenant. To request access, raise a support request.
Once you have crawled Databricks AI/BI dashboards, Atlan can build lineage connecting each dashboard to the Unity Catalog tables, columns, and metric views it reads. The same workflow populates usage and popularity metrics for your dashboards.
Dashboard lineage runs in the Databricks lineage and usage workflow—the same workflow that builds table and column lineage—not in the crawler.
Prerequisites
Before extracting dashboard lineage, make sure you have:
- Feature access enabled for your tenant: The Import AI/BI Dashboards and Enable Dashboard Lineage options stay hidden in the workflow setup until the feature is enabled. Raise a support request to request access.
- Crawled Databricks AI/BI dashboards at least once—lineage for a dashboard Atlan hasn't cataloged produces no edges
- Set up lineage and usage extraction for the same connection
SELECTonsystem.access.table_lineageandsystem.access.column_lineage, and onsystem.query.historyfor usage metrics
Extract lineage
To extract dashboard lineage:
- Follow the standard Extract lineage and usage from Databricks steps.
- Under lineage extraction, turn on Enable Dashboard Lineage.
- Run the workflow.
- After the workflow completes, open any Dashboard asset in Atlan and select the Lineage tab to view its upstream tables, columns, and metric views.
What lineage Atlan builds
Atlan reads dashboard lineage from the Unity Catalog lineage system tables and creates these relationships:
| Upstream asset | Downstream asset | Source |
|---|---|---|
| Table | Dashboard | system.access.table_lineage |
| Metric view | Dashboard | system.access.table_lineage |
| Column | Dashboard | system.access.column_lineage |
Column lineage terminates at the dashboard itself. Databricks reports which source columns a dashboard reads, but not which dashboard element consumes them, so Atlan doesn't invent a target column.
Dashboard usage metrics
When usage extraction is turned on, the same workflow populates these metrics on each dashboard from Databricks query history:
| Metric | Description |
|---|---|
| Source read count | Number of queries run against the dashboard in the lookback window |
| Source read user count | Number of distinct users who ran those queries |
| Source last read at | Timestamp of the most recent query |
| Popularity score | Derived from the read count and distinct user count |
Usage metrics cover the lookback window you configure for usage extraction, not the dashboard's entire history.
See also
- Crawl Databricks AI/BI dashboards: Discover and catalog AI/BI dashboards from your Databricks workspace.
- How Atlan builds lineage for Databricks dashboards: Understand the lineage sources, relationships created, and known limits.
- Permissions for Databricks AI/BI dashboards: Full reference of the privileges required to crawl dashboards and extract their lineage.