Organizations face three recurring data problems—inconsistent metric definitions, fragmented access controls, and metric changes that don't propagate everywhere. A semantic layer solves this by centralizing metric definitions and governance in one place, so all tools pull the same numbers and changes cascade automatically. It won't fix bad data at the source, but it shrinks the surface area you need to manage and makes self-service analytics actually work.

• The same metric getting defined differently across Tableau, Power BI, and Python isn't a minor annoyance—it's a root cause of bad executive decisions.
• Hiring more BI analysts as gatekeepers just creates ticket queues and bottlenecks; it doesn't fix fragmented governance across tools.
• A semantic layer centralizes metric definitions and access controls so a single change (e.g., redefining ARR) propagates automatically everywhere instead of requiring manual updates across systems.
• Centralizing definitions and logic in one place also makes the data self-documenting, enabling real self-service instead of ticket-based requests.

Rill’s Metrics SQL lets you define business metrics once and query them using plain SQL across dashboards, notebooks, and AI agents. It compiles metric views into optimized OLAP queries, handling grouping, filters, time functions, and security automatically.

• Define a metric once in a YAML-backed metrics view and query it as plain SQL from dashboards, notebooks, and AI agents alike, instead of redefining it in dbt, Looker, Python, etc.
• A parser/compiler/executor pipeline rewrites simple queries like "SELECT country, revenue FROM revenue_metrics" into full OLAP SQL with correct GROUP BY, joins, and filters automatically.
• Security (row-level and column permissions) and SQL-injection-safe parameter binding are enforced consistently at the executor stage for every consumer.
• Works across multiple backends (ClickHouse, Snowflake, DuckDB, Druid) and can leverage existing database optimizations like materialized views and indexes for performance.