Designing and Managing Semantic Models in Fabric

Organizations rely on clean, well-structured data to make critical business decisions, yet building a reliable single source of truth is often challenging. This course guides you through the foundational concepts of semantic modeling, helping you transform raw data into structured, high-performance reporting models. By reading and working through the practical written exercises, you will develop the skills to design, optimize, and manage enterprise-grade semantic models. You will move from understanding basic data relationships to implementing robust security and lifecycle workflows that scale. What you will learn: 1. Understand core semantic modeling concepts, terminology, and star schema design principles. 2. Write and debug foundational DAX formulas to create calculated columns, measures, and tables. 3. Configure Direct Lake and Import storage modes to balance performance and memory usage. 4. Implement row-level security and object-level security to protect sensitive organizational data. 5. Manage semantic model lifecycles using modern version control and deployment pipelines. 6. Optimize query performance through model analysis, relationship tuning, and best practices. This text-based course begins with essential data modeling definitions and architectural foundations before moving on to hands-on DAX logic and performance optimization. You will then explore advanced governance, data access control, and modern deployment strategies to ensure your models remain reliable and secure. This course is designed for beginner data analysts, business intelligence enthusiasts, and aspiring data engineers who want to learn semantic modeling in Fabric from scratch. No prior data modeling experience is required. Start reading today to build trust in your organization's data.