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databricks-metric-views

Define and manage Unity Catalog metrics with YAML definitions.

1|Updated Mar 17, 2026
Search Tags:#yaml#data-modeling#joins#databricks#unity-catalog#metric-views#dimensions-measures
One-click install
npx skills add https://github.com/leary-poken/ai-dev-kit --skill databricks-metric-views-leary-poken
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: databricks-metric-views
Source: https://github.com/leary-poken/ai-dev-kit/tree/main/databricks-skills/databricks-metric-views
Command: npx skills add https://github.com/leary-poken/ai-dev-kit --skill databricks-metric-views-leary-poken

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Unity Catalog metric views provide a YAML-based mechanism to define, deploy, and query governed business metrics, enabling consistent KPI definitions across teams and tools.

Core Features & Use Cases

  • Define standardized business metrics (revenue KPIs, order analytics) in a single YAML definition.
  • Build KPI layers shared across dashboards, Genie, and SQL queries, with flexible dimensions and measures.
  • Enable pattern-rich metric models with joins, window measures, and optional materialization for pre-computation.

Quick Start

Save a YAML metric view definition under your catalog/schema and query it via MEASURE() in SQL.

Frequently Asked Questions about databricks-metric-views

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

FAQPage Schema
How do I define standardized business metrics in Unity Catalog using YAML?▼

To standardize business metrics in Unity Catalog, you write a YAML metric view definition specifying required dimensions and measures, then query it via the MEASURE() function in SQL.

What are Unity Catalog metric views and when do I need them?▼

Unity Catalog metric views are YAML-based definitions that deploy and query governed business metrics, enabling consistent KPI definitions across cross-team dashboards, Genie queries, and SQL analytics.

Does the YAML metric view specification support joins and materialization?▼

Yes, the YAML metric view specification supports joins and optional materialization for pre-computation, alongside pattern-rich metric models with window measures for advanced data analytics.

Can I use YAML metric views to build a shared KPI layer for Databricks dashboards and Genie?▼

Yes, you can build a shared KPI layer for Databricks dashboards and Genie by defining your revenue and order analytics metrics once in a single YAML metric view definition.

What are the minimum requirements for a Unity Catalog YAML metric view definition?▼

The minimum requirements for a YAML metric view definition are conforming to spec version 1.1 or 0.1 and including at least one dimension and one measure within the structure.

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