Overview

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This course teaches advanced strategies for optimizing data models and improving performance in Power BI and Microsoft Fabric. Learners will gain the skills needed to build efficient, secure, and scalable BI solutions in complex data environments. Participants will explore Microsoft Fabric’s architecture, semantic model refresh strategies, storage modes, and intermediate data stores. By mastering these concepts, learners can enhance solution efficiency, streamline report distribution, and improve overall BI performance. What makes this course unique is its combination of theoretical knowledge with hands-on optimization techniques. Real-world scenarios demonstrate how to secure semantic models, tune performance, and deploy robust BI solutions effectively. This course is designed for BI developers, data engineers, and IT professionals seeking to elevate their skills in Power BI and Microsoft Fabric. A working knowledge of Power BI and basic data modeling is recommended. This course is part two of a three-course Specialization designed to provide a comprehensive learning pathway in this subject area. If you haven't already explored part 1, then learners are encouraged to complete that course before starting this one.

Syllabus

Understanding Microsoft Fabric

This module introduces the architecture and core components of Microsoft Fabric, highlighting its integration with Power BI and data storage solutions like Lakehouse and Data Warehouse. Learners will explore how semantic models are automatically generated and how to build them using Direct Lake connectivity. By the end, you'll understand how Fabric supports modern data analytics workflows.

Managing Semantic Model Refresh

This module explores various methods for refreshing semantic models in Power BI, including full and incremental refresh strategies. Learners will gain hands-on experience using XMLA endpoints and decision trees to select the most efficient refresh approach for different scenarios. Practical guidance is provided for managing large datasets and optimizing refresh operations.

Performing Optimizations in Power BI

This module guides learners through essential techniques for optimizing Power BI semantic models, including best practices for column and relationship design. Learners will explore powerful tools like VertiPaq Analyzer, Tabular Editor, and Performance Analyzer to diagnose and enhance report performance. Practical strategies for connector selection, streaming operations, and DAX optimization are also covered to ensure efficient and responsive Power BI solutions.

Managing Semantic Model Security

This module explores essential strategies for securing semantic models in Power BI, focusing on user access control and data residency considerations. Learners will gain practical knowledge on configuring security settings and understanding how data storage locations impact compliance and governance.

Performing Power BI Deployments

This module guides learners through the process of deploying Power BI solutions, including the use of deployment pipelines and Git integration for streamlined change management. Participants will explore best practices for report development, environment management, and leveraging Azure DevOps for version control. By the end, learners will be equipped to efficiently publish and manage Power BI artifacts in organizational settings.