Fabric Data Modeling and Performance Optimization for Beginners

As data volumes grow, poorly designed data models can lead to slow reports and high computing costs. Understanding how to structure and optimize your data within Fabric is essential for building fast, scalable analytics solutions. This course guides you from the absolute basics of data warehousing to implementing efficient data structures and optimizing query performance. What you'll learn: 1. Understand foundational data modeling concepts, including star schemas, facts, and dimensions. 2. Configure Fabric's Direct Lake mode to connect Power BI reports directly to Delta tables for maximum speed. 3. Apply partitioning and indexing strategies to optimize storage and query performance. 4. Design clean data pipelines using the medallion architecture of bronze, silver, and gold layers. 5. Identify performance bottlenecks in DAX queries and data loading processes. 6. Practice structuring tables and writing optimized queries through written scenarios. You will start with core storage definitions and relational design principles before moving into storage formats and performance-tuning techniques. The material is structured to build your confidence step-by-step through clear written explanations and practical architectural walkthroughs. This course is designed for beginners, data analysts, and aspiring data engineers who want to build faster reporting systems, with no prior data engineering experience required. Start reading today to unlock the full performance potential of your data platform.