🧠 Can Databricks Replace Your BI Semantic Layer? Yes —BUT…

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Why Semantic Layers Matter (Now More Than Ever)

In today’s fast-paced world of analytics and AI, organizations are struggling with a familiar problem: everyone defines data differently.

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Marketing’s definition of “active user” doesn’t match Product’s. Finance’s “net revenue” calculation shifts depending on the dashboard. And every analyst writes their own version of “the truth” in SQL.

Enter the semantic layer — the unsung hero of governed analytics.

A semantic layer bridges the gap between raw data and business meaning. It provides a consistent, centralized definition of metrics and dimensions, allowing everyone to speak the same data language — from SQL developers to business analysts using Power BI or Tableau.

Traditionally, semantic layers were the domain of OLAP cubes or BI tools. But with the rise of lakehouses, Databricks, and governed data lakes, we now need to rethink how and where the semantic layer lives.

💡 Can You Build a Semantic Layer Inside Databricks?

Absolutely. And Databricks is getting better at it by the month.