Copilot can make a governed Power BI semantic model easier to explore, but it cannot repair unclear definitions, duplicate fields, weak relationships, or unreliable data. Learn how to curate, secure, document, and test a model before business users query it in natural language.
Power BI Import, DirectQuery, and Direct Lake have different query paths, freshness patterns, and operating requirements. This practical guide explains the trade-offs and shows how to choose a storage mode for a real semantic-model workload.
Measures answer dynamic questions in the current report context. Calculated columns create stored row-level fields for categorization and model design. Learn how to choose between them—and when Power Query or the source system is a better fit.
A slow Power BI report is not automatically a DAX problem. Use a measure-first workflow to identify whether the delay comes from a visual, semantic model, source query, refresh process, gateway, or capacity—and validate improvements without changing business results.
A star schema is often the clearest default for a Power BI semantic model, but a snowflake schema can be justified by governance, reuse, or source constraints. Learn how each design affects relationships, report authoring, DAX, and model maintenance.
Build Power BI semantic models that remain correct, understandable, and responsive as they grow. This guide covers grain, star schemas, relationships, reusable measures, storage modes, governance, and a repeatable process for diagnosing slow reports.