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databricks-aibi-dashboards

Build validated Databricks AI/BI dashboards from tested SQL datasets.

Updated Mar 19, 2026
Search Tags:#validation#dashboard#sql#filters#widgets#databricks#lakeview
One-click install
npx skills add https://github.com/Blackkadder/databricks-apps-and-agents-workshop --skill databricks-aibi-dashboards-blackkadder
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: databricks-aibi-dashboards
Source: https://github.com/Blackkadder/databricks-apps-and-agents-workshop/tree/main/.claude/skills/databricks-aibi-dashboards
Command: npx skills add https://github.com/Blackkadder/databricks-apps-and-agents-workshop --skill databricks-aibi-dashboards-blackkadder

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Databricks AI/BI dashboards often break at deploy time due to untested SQL, mismatched widget field names, incorrect widget versions, and invalid layout rules; this Skill ensures dashboards are built correctly and reliably before deployment.

Core Features & Use Cases

  • Validated Deployment Workflow: Enforces a mandatory workflow to inspect table schemas, write dataset SQL, and TEST EVERY QUERY via execute_sql before assembling dashboard JSON.
  • Widget and Layout Guardrails: Documents explicit rules for widget versions, field-name contracts, text widget behavior, filter scopes (global vs page-level), sizing, and 6-column grid layout to avoid runtime errors.
  • Use Case: Build a production sales or operations dashboard with counters, charts, tables, and global filters that consistently render and refresh when backed by scheduled pipeline outputs.

Quick Start

Create a dashboard by designing datasets with fully qualified SQL, test each query with execute_sql, assemble widgets following the naming, version, and layout rules, then deploy using create_or_update_dashboard.

Frequently Asked Questions about databricks-aibi-dashboards

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I prevent Databricks Lakeview dashboards from breaking at deploy time?▼

To prevent Lakeview dashboards from breaking, test every SQL query via execute_sql and enforce strict widget field-name matching, layout constraints, and version rules before deploying.

What is the best way to build validated Databricks AI/BI dashboards with SQL datasets?▼

The best way to build validated Databricks AI/BI dashboards is to inspect table schemas, write fully qualified SQL, test queries via execute_sql, and deploy using create_or_update_dashboard.

How do I configure global and page-level filters for Databricks AI/BI dashboards?▼

Configuring global and page-level filters for Databricks AI/BI dashboards requires following explicit widget versioning, field-name contracts, and 6-column grid layout rules to avoid runtime errors.

Why do my Databricks dashboard widgets fail to render after deploying SQL datasets?▼

Dashboard widgets fail to render due to untested SQL, mismatched widget field names, incorrect widget versions, or invalid layout rules, which you can prevent by testing queries before assembly.

Can I use counters, tables, and charts together in a Databricks Lakeview dashboard?▼

Yes, you can use counters, tables, and charts together in a Lakeview dashboard by assembling widgets following strict naming, version, and 6-column grid sizing rules before deployment.

Do I need to test every SQL query before deploying a Databricks AI/BI dashboard?▼

Yes, you must test every SQL query using execute_sql before assembling dashboard JSON to ensure your Databricks AI/BI dashboard consistently renders and refreshes without runtime errors.

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