databricks-aibi-dashboards

To create Databricks AI/BI dashboards, you must first validate all SQL queries against your Unity Catalog data. This ensures underlying data queries are tested before generating the compliant dashboard JSON, preventing invalid widget errors.

Invalid widget errors in Databricks Lakeview dashboards typically occur when SQL queries are not validated prior to deployment. Enforcing a strict validation workflow for SQL and JSON structure prevents these common errors and ensures best practices.

Yes, you can build interactive dashboards with counters, charts, tables, and filters on Unity Catalog data. The process involves structured dashboard creation that adheres to specific widget types, versions, and layout rules.

The best way to structure JSON for Databricks AI/BI dashboards is by following a guided creation process that enforces specific widget types, versioning, layout rules, and field matching to ensure full compliance with platform standards.

Yes, the Databricks AI/BI dashboard creation process supports custom filters and KPI tables. It guides the building of compliant JSON for interactive dashboards, ensuring all underlying data queries are validated first.

Building dashboards without validating SQL first leads to invalid widget errors and non-compliant JSON structures. A mandatory validation workflow is required to test queries, ensure correct field matching, and maintain proper widget versioning.