Semantic Layer Best Practices: 7 Mistakes to Avoid

Semantic layers don't fail because the technology is wrong. They fail because of design decisions made in the first two weeks — choices that seem reasonable at the time and create compounding problems for months afterward. Here are the seven mistakes that kill semantic layer projects, and how to avoid each one. Mistake 1: Defining Metrics in Multiple Places What happens : Revenue is defined in a Tableau calculated field, a Power BI DAX measure, a dbt model, and a SQL view. Four sources of truth. None of them agree. Why it's common : Teams adopt new tools without migrating metric definitions. Each tool gets its own model. Over time, the definitions drift. The fix : Every metric gets exactly one canonical definition in the semantic layer. All downstream tools query that definition. No exceptions. When someone needs Revenue, they query business.revenue , not their own formula. This principle extends to AI agents. If your AI generates its own metric formulas instead of referencing the sema