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Unity Catalog business semantics is a centralized platform for defining and managing business metrics and KPIs. Standardized metric definitions promote consistent reporting across your organization and give AI tools the context they need to interpret your data accurately, with governance enforced through Unity Catalog.
Business semantics consists of two integrated components:
- Metric views: Reusable SQL objects that define and govern business KPIs.
- Agent metadata: Synonyms, display names, and formatting rules that help AI tools interpret your data in business terms.
Explore the tools and resources on this page to start working with Unity Catalog business semantics.
Get started
Use the following pages to create, query, and manage business semantics.
| Page | Description |
|---|---|
| Unity Catalog metric views | Learn what metric views are, why they're more flexible than standard views, and how they fit into the Databricks platform. |
| Create and edit metric views | Define metric views using SQL DDL or the Catalog Explorer UI, with built-in YAML validation. |
| Query metric views | Query metric views from SQL editors, notebooks, dashboards, Genie spaces, and external tools. |
| Tutorial: Build a complete metric view with joins | Walk through a complete sales analytics metric view with joins, measures, and agent metadata using the TPC-H dataset. |
Model and optimize
Use the following pages to define and optimize your metric view data models.
| Page | Description |
|---|---|
| Model metric views | Define sources, dimensions, measures, filters, and star and snowflake schema joins. |
| Advanced techniques for metric views | Build complex metrics using composability and window measures for time-series analysis. |
| Materialization for metric views | Pre-compute and incrementally refresh aggregations to improve query performance. The query engine automatically rewrites queries to use materialized views when appropriate. |
| Agent metadata in metric views | Add synonyms, display names, and formatting rules to improve AI agent accuracy and dashboard readability. |
Manage and reference
Use the following pages to manage metric view access and find syntax reference information.
| Page | Description |
|---|---|
| Manage metric views | Control access, enable collaborative editing, and manage the metric view lifecycle using Catalog Explorer or SQL. |
| Metric view YAML syntax reference | Complete reference for the metric view YAML specification, including all fields, types, and formatting examples. |