# Databricks SQL and BI

Design the SQL layer as a governed product surface, not as a pile of dashboards attached to an
unowned warehouse. The semantic definition, data permissions, compute policy, refresh behavior,
and business owner all need a home.

## Surface map

| Need | Start with | Guardrail |
|---|---|---|
| Interactive SQL and BI connectivity | SQL warehouse | Size, autoscaling, timeout, tags or budget policy, and owner |
| Governed reusable business metrics | Curated views or metric views | One definition, reviewed dimensions, tests, and lineage |
| Managed internal reporting | AI/BI dashboards | Certified source, refresh owner, subscriptions, and access review |
| Natural-language exploration | Genie | Curated data, instructions, representative questions, and answer evaluation |
| External BI tool | Native connector to a SQL warehouse | SSO or service principal, network path, query limits, and import/direct mode |

## Production baseline

1. Publish a small, documented semantic layer instead of exposing every bronze and silver table.
2. Grant access to groups at the catalog or schema boundary and narrow it only where required.
3. Separate interactive, scheduled, and heavy transformation workloads when one can starve the
   others or make attribution ambiguous.
4. Set a warehouse owner, cost attribution, idle timeout, scaling bounds, and query monitoring.
5. Test dashboards and semantic definitions as code where possible: schema, row counts, key
   metrics, freshness, and permission expectations.
6. Evaluate Genie with real business questions and known answers. Treat confident unsupported
   answers as failures, not as a user-training problem.
7. Review sharing, export, download, and subscription paths; read access is not the only egress.

## Review questions

- Which definition is authoritative when two dashboards calculate the same metric differently?
- Can every dashboard tile be traced to a governed object and an accountable owner?
- Which workload pays for an expensive query, and what prevents accidental unbounded scans?
- Does the connection preserve the end user's identity, or does everyone inherit one service
  principal's access?
- What alerts when a dashboard is fresh but wrong because an upstream contract changed?

## Official sources

- Databricks SQL — https://learn.microsoft.com/azure/databricks/sql/
- AI/BI dashboards — https://learn.microsoft.com/azure/databricks/dashboards/
- Genie — https://learn.microsoft.com/azure/databricks/genie/