Optimizing Data Models and Performance in Microsoft Fabric

Coursera MOOC / Non-credit USD 49
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Optimizing Data Models and Performance in Microsoft Fabric

About this course

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.

What you'll learn

  • build efficient and scalable BI solutions
  • improve performance tuning techniques
  • secure semantic models

Course objectives

  • enhance solution efficiency
  • streamline report distribution
  • understand Microsoft Fabric's architecture

Skills you'll gain

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