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Databricks AI/BI Dashboards

AI/BI Dashboards are the first-party Databricks dashboard surface that resolves Metric View MEASURE() calls against DBSQL warehouses, with governance + lineage flowing through Unity Catalog. They are one of four named consumers of Metric Views disclosed in the BI Serving Pointers source (alongside Genie, SQL notebooks, and third-party BI tools). (Source: sources/2026-05-27-databricks-bi-serving-pointers-maximizing-for-performance-and-tco)

What it is

A Databricks-resident dashboarding tool that:

  • Connects to a DBSQL warehouse for query execution.
  • Resolves Metric View MEASURE() calls against UC-governed metric definitions.
  • Inherits UC access control (row filters, column masks, RBAC) for the underlying tables.
  • Composes with Genie for embedded natural-language query inside dashboard widgets.
  • Is queryable from the same metv_* Metric Views as Genie and SQL notebooks — "the dashboard and Genie examples above both queried the same Metric View, and both had their queries transparently routed to a materialization".

Position in the stack

   AI/BI Dashboards  ◄── this page
       │
       ▼ MEASURE(metric)
   Metric Views (UC semantic layer)
       │
       ▼ query rewriting
   Pre-aggregated materialization
       │
       ▼
   UC managed tables (Liquid Clustering + Predictive Optimization)

The architectural value: the dashboard widget queries the same governed metric definition as every other consumer, so the revenue number on the dashboard matches the revenue number from Genie and from the SQL notebook.

Operational shape

  • The source's worked example shows a warehouse-metrics dashboard queried from the metv_dbsql_metrics Metric View — reflexively monitoring the warehouse via the same primitive the warehouse serves.
  • Dashboard queries hit the same DBSQL caching tiers (disk cache + QRC) as any other consumer; high-traffic dashboards benefit from QRC near-miss patterns when many users view the same widget.
  • The recommendation in the source: "Monitor the results — point dashboards at Metric Views and track query performance via system tables."

Caveats

  • The source is a vendor walkthrough; the dashboard product's full feature surface (widget types, drill-down semantics, embedding into other apps) is not covered here.
  • Cross-references to the embedded-iframe pattern from the Cloudflare Skipper source (patterns/embedded-dashboard-with-zero-trust-iframe) are architectural, not Databricks-AI/BI-specific.

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