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databricks-aibi-dashboards

Design and deploy Databricks AI/BI dashboards with validated SQL queries.

1|1|Updated Oct 1, 2025
Search Tags:#dashboard#data-quality#databricks#ai-bi#dashboard-deployment#sql-validation#execute_sql
One-click install
npx skills add https://github.com/mkgs-databricks-demos/synthea-on-fhir --skill databricks-aibi-dashboards-mkgs-databricks-demos
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: databricks-aibi-dashboards
Source: https://github.com/mkgs-databricks-demos/synthea-on-fhir/tree/main/.cursor/skills/databricks-aibi-dashboards
Command: npx skills add https://github.com/mkgs-databricks-demos/synthea-on-fhir --skill databricks-aibi-dashboards-mkgs-databricks-demos

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Create Databricks AI/BI dashboards with strictly validated SQL queries, reducing deployment errors and rework.

Core Features & Use Cases

  • Create end-to-end Databricks dashboards by assembling datasets, pages, and widgets.
  • Enforce a mandatory validation workflow where all SQL queries are tested via execute_sql before deployment.
  • Use the provided MCP tooling to fetch table schemas, test queries, and deploy dashboards deterministically.

Quick Start

Create a dashboard by first validating all queries with execute_sql, then assemble datasets, pages, and widgets and deploy via 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 validate SQL queries before deploying a Databricks AI/BI dashboard?▼

To validate SQL queries for Databricks AI/BI dashboards, you must test all SQL statements using execute_sql before assembling datasets, pages, and widgets. This strict validation workflow ensures deterministic data pipelines and reduces deployment rework.

What is the process to create Databricks AI/BI dashboards with validated datasets?▼

Creating Databricks AI/BI dashboards involves fetching table schemas via get_table_details, validating all SQL queries using execute_sql, and then assembling datasets, pages, and widgets before deploying deterministically using create_or_update_dashboard.

Can I use this approach to deploy dashboards across multiple data domains?▼

Yes, this dashboard deployment workflow applies to datasets across multiple domains. It ensures every dataset has verified queries via execute_sql and proper dashboard structuring before deploying across different data domains.

Why does my Databricks dashboard deployment fail without strict SQL validation?▼

Dashboard deployments often fail or require rework without strict SQL validation because untested queries cause structural errors. Enforcing a mandatory validation workflow where all SQL queries are tested via execute_sql before deployment ensures deterministic data pipelines and reduces errors.

Do I need to fetch table schemas manually before building AI/BI dashboards?▼

You do not need to fetch table schemas manually outside the provided tooling. The workflow uses the get_table_details MCP tool to automatically obtain dataset schemas, ensuring proper dashboard structuring before deploying via create_or_update_dashboard.

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