Summary
In this module, you learned how data warehouses use dimensional modeling to organize data into fact and dimension tables, and what makes a Fabric data warehouse unique. You explored querying and transforming data with T-SQL and the visual query editor, structured tables into a star schema, and applied security features like row-level security and dynamic data masking to protect your data.
Without a platform like Microsoft Fabric, building this kind of warehouse environment would require provisioning and managing dedicated SQL infrastructure, configuring separate storage and compute, and manually integrating data across siloed systems. A Fabric data warehouse eliminates that complexity by combining full T-SQL capabilities with OneLake integration in a single, governed platform that supports both traditional analytics and AI-powered experiences.
To learn advanced T-SQL transformation patterns like staging workflows, incremental loads, and MERGE-based upserts, continue to the Transform data using T-SQL module.