Build the semantic layer that makes AI analytics trustworthy
AI analytics is only as good as the context you give it. Without a semantic layer - a unified, shared definition of metrics, segments, and business logic - AI (and everyone else) is guessing at what "active user" or "revenue" means at your company. Data Studio is the analyst workbench where that foundation gets built. Define metrics once. Transform raw tables using SQL or Python. See dependencies before changing anything. Publish what's trusted to your Library. Then get reliable answers from AI
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