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ScottHMcKean
ScottHMcKeanCOMMUNITY
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databricks-metric-views

Manage governed business metrics in Databricks Unity Catalog with declarative YAML.

3|Updated Jan 2, 2025
Search Tags:#metrics#data modeling#business intelligence#kpis#databricks#unity catalog
One-click install
npx skills add https://github.com/ScottHMcKean/genai_notebooks --skill databricks-metric-views-scotthmckean
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: databricks-metric-views
Source: https://github.com/ScottHMcKean/genai_notebooks/tree/main/.cursor/skills/databricks-metric-views
Command: npx skills add https://github.com/ScottHMcKean/genai_notebooks --skill databricks-metric-views-scotthmckean

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill standardizes the definition and querying of business metrics, ensuring consistency across teams and tools by managing them through Unity Catalog.

Core Features & Use Cases

  • Standardized KPIs: Define reusable metrics like revenue, conversion rates, etc.
  • Complex Aggregations: Build metrics with ratios, filtered measures, and window functions (moving averages, YTD).
  • Schema Modeling: Define star and snowflake schemas declaratively.
  • Use Case: Create a "Monthly Recurring Revenue" metric that is consistently defined and accessible to all analysts and dashboards, preventing discrepancies.

Quick Start

Use the databricks-metric-views skill to create a metric view for orders with dimensions for month and status, and measures for order count and total revenue.

Frequently Asked Questions about databricks-metric-views

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

FAQPage Schema
How do I standardize business metrics and KPIs in Databricks Unity Catalog?▼

Define governed business metrics in Databricks Unity Catalog using a declarative YAML syntax. This standardizes KPIs like revenue or conversion rates, ensuring cross-team consistency and preventing dashboard discrepancies.

Can I define complex aggregations and window functions for business metrics in Databricks?▼

Yes, you can define complex aggregations for business metrics including ratios, filtered measures, and window functions. This supports advanced KPI modeling such as calculating moving averages and year-to-date totals within your metric definitions.

What is the best way to model star schemas for business intelligence in Databricks?▼

Model star and snowflake schemas declaratively using YAML syntax for business intelligence in Databricks. This defines dimensions and measures, standardizing data modeling for KPI development across teams.

How do I create a metric view for order dimensions and measures in Databricks?▼

Create a metric view for orders by defining dimensions like month and status alongside measures for order count and total revenue. This declarative approach standardizes metric definitions for consistent querying across analysts.

Does this approach to metric management require Unity Catalog?▼

Yes, managing governed business metrics through this approach relies on Databricks Unity Catalog. It leverages Unity Catalog to standardize metric definitions, ensuring consistency and governance across teams and BI tools.

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