malloy-discover

Automating data discovery for Malloy modeling involves silently scanning tables, columns, distributions, and relationships to build an internal picture of the data before presenting findings for informed modeling decisions.

Silent data scanning in the Malloy workflow is an automated process that inspects tables, columns, and relationships to prepare an internal data picture, streamlining initial data exploration without requiring user interaction.

Yes, you need access to Malloy models and MCP tools for data inspection to automatically scan tables, columns, distributions, and relationships during the initial data discovery phase.

The best way to prepare data for a new Malloy model is to activate automated data discovery, which scans available data distributions and relationships to provide quick insights for modeling decisions.

Yes, you can use automated data scanning for initial data exploration in Malloy to quickly understand available data, distributions, and relationships before making informed modeling decisions.

Malloy data discovery scans relationships before presenting findings to build a complete internal data picture, ensuring the initial exploration phase fully understands the data structure for accurate modeling preparation.