Unity Catalog Metric Views

Define reusable, governed business metrics in YAML that separate measure definitions from dimension groupings for flexible querying.

When to Use

Use this skill when:

• Defining standardized business metrics (revenue, order counts, conversion rates)
• Building KPI layers shared across dashboards, Genie, and SQL queries
• Creating metrics with complex aggregations (ratios, distinct counts, filtered measures)
• Defining window measures (moving averages, running totals, period-over-period, YTD)
• Modeling star or snowflake schemas with joins in metric definitions
• Enabling materialization for pre-computed metric aggregations

First: can this even be a metric view? (decision gate)

Before authoring, confirm the measure re-aggregates at query time. Additive SUM/COUNT, a COUNT(DISTINCT) that recomputes per cell, MEASURE() ratios (divide last), and supported window measures (trailing / cumulative / period-over-period — Pattern 8) all re-aggregate correctly and are valid metric-view measures; this list is not exhaustive. The gate below is about disqualifying shapes — if any of the following hold, it is not a metric view: author a governed Unity Catalog SQL function instead (build it with databricks-dbsql) and expose it to Genie as a trusted registered SQL function (Design Priorities surface #11), rather than forcing it into a view or a pre-aggregated helper view: