Creating a Semantic Model in Microsoft Fabric Warehouse

Introduction

Imagine you’ve spent weeks designing a data warehouse. Tables are loaded, data is clean, and performance is solid. You run a few SQL queries and feel proud. But when your business users ask for a simple “sales by region” report, you realize they’re staring at raw table names, cryptic column codes, and have no clue where to begin.

This is the moment you need a semantic model, the translator between raw data and real insights.

Welcome to Microsoft Fabric Warehouse, where the semantic model transforms your curated data into something that business users, analysts, and Power BI can understand and use. In this article, we’ll explore what a semantic model is, why it matters, and how to build one from scratch in Microsoft Fabric Warehouse.

What is a Semantic Model?

A semantic model is a business-friendly layer that sits on top of your warehouse data. It defines.

• Relationships between tables
• Measures like "Total Sales" or "Profit Margin"
• KPIs and hierarchies
• Business logic in DAX
• Human-readable metadata

This layer enables Power BI reports to query data meaningfully without requiring users to write complex SQL or understand schema diagrams.

Why Use Semantic Models in Fabric Warehouse?

With Microsoft Fabric bringing together Power BI, Synapse, and Data Factory into a unified platform, semantic models play a critical role in.

• Self-service analytics
• Governed datasets with shared definitions
• Reusability across reports and dashboards
• Centralized business logic
• Performance optimization via pre-aggregations and models

And best of all, you can build semantic models directly from your Fabric Warehouse.

Let’s Build a Semantic Model in Fabric Warehouse

Here’s how to go from raw warehouse tables to a ready-to-use semantic model.

✅ Prerequisites

Before you begin, make sure

• You have a Fabric Warehouse with tables (e.g., Sales, Products, Regions)
• You’re assigned a role with permission to create semantic models
• You have access to a workspace in Microsoft Fabric

Step-by-Step Guide

In this article, I've already created a Fabric Warehouse named Sales_WH containing two tables, orders and customers, as seen below.

To create a new semantic model, click on the New semantic model in the Reporting tab of the warehouse. This automatically launches the New semantic model widow.

Select tables to be the new semantic model on, and provide a unique name for the semantic model. In this article, Orders_by_customers_semantic_model is used.

Click Continue

In less than 1 minutes, the semantic model is ready for upstream consumption. To check tt, navigate to the workspace where the Fabric Warehouse is housed. As seen in the screenshot below, we can see the newly created Orders_by_customers_semantic_model, and we are ready to use it to build reports.

To see more details about the semantic model, click on it and that takes you to the Details page as seen below.

In conclusion, in a world drowning in data, a semantic model is your life raft. It transforms cold, raw warehouse tables into warm, digestible, self-service data experiences.

Thanks to Microsoft Fabric's tight integration of warehouses, Power BI, and semantic modeling, building these models is now faster, easier, and more powerful than ever.

So the next time your team says.

“Can we just get a dashboard that shows total sales by region and product?”

You’ll say,

“Already built. It’s in the semantic model. Just open Power BI.”