Master the essential schema design methodologies that power effective data warehouses through practical implementation of different modeling approaches. You'll design and implement star schemas with fact and dimension tables, transform these into snowflake schemas for complex dimensional modeling, apply data vault techniques for enterprise data integration, and develop a decision framework for selecting the right schema based on specific business requirements. Through hands-on modeling exercises, you'll gain the skills to design schemas that balance query performance, data integrity, and business adaptability across various analytical scenarios.

Optimize data warehouse performance and reliability through advanced table configurations and transaction management techniques. You'll learn to distinguish between distributed and replicated tables to maximize query efficiency, learn how Fabric manages columnar storage and measure query performance, design multi-table transactions with proper error handling, and create scalar user-defined functions to standardize calculations. Through comparative performance analysis and hands-on implementation, you'll develop the technical skills needed to fine-tune your data warehouse for optimal performance while maintaining data integrity across complex operations.

Design and implement scalable data integration solutions using Microsoft Fabric's Data Factory capabilities. You'll explore the Data Factory interface and components, create both ETL and ELT pipelines for different data processing scenarios, implement parameterization and control flow logic for flexible pipeline design, and establish effective monitoring and troubleshooting practices. Through guided demonstrations and hands-on pipeline development, you'll gain practical experience building maintainable data workflows that reliably integrate data across your organization's data estate.

Advance your data engineering capabilities with sophisticated transformation strategies and modern DevOps practices for data workflows. You'll compare different transformation approaches using dataflows, notebooks and SQL, implement visual and code-based transformations, configure delta pipeline integration with schema evolution handling, and establish CI/CD pipelines using Git for version control. This module culminates in a comprehensive implementation of collaborative development workflows that enable teams to reliably develop, test, and deploy data solutions while maintaining quality and governance throughout the process.