Snowflake promotes data quality and semantic layer capabilities for analytics

Snowflake has introduced Data Metric Functions (DMFs), a native feature that lets organizations continuously monitor data quality inside the platform. DMFs return metrics such as null counts, distinct values and table freshness, can be applied to tables, views and other objects, run automatically on a defined schedule and store results in a dedicated event table, enabling ongoing visibility and comparison. Both system‑provided and custom DMFs are supported, though limits exist on the number of assignments and on usage in shared or trial accounts.

A semantic layer provides shared business logic that translates raw data into consistent definitions of metrics, dimensions and governance rules. By serving as a single source of truth, it ensures that dashboards, query editors, data‑science notebooks and AI‑driven interfaces return identical answers, improves self‑service access, and embeds security and certification policies. The concept dates back to the 1990s with early tools such as MicroStrategy.