azure-databricks

Provision Azure Databricks workspaces with Unity Catalog governance via az CLI.

Updated Apr 27, 2026
One-click install
npx skills add https://github.com/tomz/agent-skills --skill azure-databricks-tomz
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: azure-databricks
Source: https://github.com/tomz/agent-skills/tree/main/azure-databricks
Command: npx skills add https://github.com/tomz/agent-skills --skill azure-databricks-tomz

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Azure Databricks provisioning and governance at scale: automates creation and configuration of workspaces, Unity Catalog governance, cluster and SQL warehouse setup, and security controls to enable consistent data platforms.

Core Features & Use Cases

  • Workspace provisioning: create and configure Azure Databricks workspaces with standard governance guardrails.
  • Unity Catalog governance: centralized data governance, catalogs, schemas, and access control across workspaces.
  • Delta Lake & data lifecycle: manage Delta Lake tables, time travel, VACUUM, and optimized data layouts.
  • MLflow integration: track experiments, model registries, and serving endpoints with Unity Catalog-backed registries.
  • Jobs & workflows: orchestrate notebooks and jobs for end-to-end data pipelines.
  • Security & secrets: manage secret scopes and access policies for secure workflows.
  • CLI & automation: end-to-end provisioning via az databricks and databricks CLI.

Quick Start

Provision an Azure Databricks workspace with Unity Catalog using the az CLI and the Databricks CLI.

Frequently Asked Questions about azure-databricks

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

FAQPage Schema
How do I provision an Azure Databricks workspace with Unity Catalog using CLI?

You can provision an Azure Databricks workspace with Unity Catalog by using the az CLI for initial setup and the Databricks CLI to configure centralized governance, catalogs, schemas, and access controls across workspaces.

What is the best way to manage Delta Lake tables and data lifecycle in Azure Databricks?

Managing Delta Lake tables in Azure Databricks involves handling time travel, running VACUUM operations, and optimizing data layouts to maintain scalable data pipelines and efficient data lifecycle governance.

Can I integrate MLflow model registries with Unity Catalog in Azure Databricks?

Yes, MLflow integration supports tracking experiments, model registries, and serving endpoints, specifically utilizing Unity Catalog-backed registries to ensure governed machine learning workflows.

How do I orchestrate end-to-end data pipelines in Azure Databricks?

You orchestrate end-to-end data pipelines in Azure Databricks by configuring Jobs and workflows to schedule and execute notebooks, ensuring automated data engineering tasks run consistently at scale.

Does Azure Databricks support secure secret management for data pipelines?

Azure Databricks supports secure secret management by allowing you to manage secret scopes and access policies, ensuring that sensitive credentials used in data workflows remain protected.

Do I need az CLI and Databricks CLI to automate Azure Databricks provisioning?

Yes, end-to-end automation for provisioning and managing Azure Databricks workspaces, clusters, and SQL warehouses relies on guided automation using both the az CLI and the Databricks CLI.