A Power BI semantic model is enterprise-ready when its measures, dimensions, relationships, security and refresh logic are documented, governed and reusable across reports. It should reduce arguments about numbers, not multiply them.
1. KPI definitions have owners
Every important metric needs a business owner and a technical expression. If revenue, margin or active customer can mean different things in different reports, the model is not ready for enterprise decision-making.
2. Measures are reusable, not hidden in reports
Core DAX measures should live in the semantic model with clear names and descriptions. Report-level improvisation may be fast at first, but it creates inconsistent numbers later.
3. Security is part of the model
Role-level security, workspace permissions and app audiences need to match the real operating model. A trustworthy model protects access without making every report a custom exception.
4. Refresh and lineage are understandable
Business users do not need pipeline internals, but they do need confidence in data freshness, source ownership and known limitations.
5. AI and NLQ use the same definitions
Natural language query and agents become safer when they work from curated measures and business terms instead of raw source tables.
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