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Microsoft Power BI Performance Best Practices

You're reading from   Microsoft Power BI Performance Best Practices Learn practical techniques for building high-speed Power BI solutions

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Product type Paperback
Published in Aug 2024
Publisher Packt
ISBN-13 9781835082256
Length 346 pages
Edition 2nd Edition
Languages
Tools
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Authors (2):
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Thomas LeBlanc Thomas LeBlanc
Author Profile Icon Thomas LeBlanc
Thomas LeBlanc
Bhavik Merchant Bhavik Merchant
Author Profile Icon Bhavik Merchant
Bhavik Merchant
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Toc

Table of Contents (23) Chapters Close

Preface 1. Part 1: Architecture, Bottlenecks, and Performance Targets
2. Chapter 1: Setting Targets and Identifying Problem Areas FREE CHAPTER 3. Chapter 2: Exploring Power BI Architecture and Configuration 4. Chapter 3: Learning the Tools for Performance Tuning 5. Part 2: Performance Analysis, Improvement, and Management
6. Chapter 4: Analyzing Logs and Metrics 7. Chapter 5: Optimization for Storage Modes 8. Chapter 6: Third-Party Utilities 9. Chapter 7: Performance Governance Framework 10. Part 3: Fetching, Transforming, and Visualizing Data
11. Chapter 8: Loading, Transforming, and Refreshing Data 12. Chapter 9: Report and Dashboard Design 13. Part 4: Data Models, Calculations, and Large Semantic Models
14. Chapter 10: Dimensional Modeling and Row Level Security 15. Chapter 11: Improving DAX 16. Chapter 12: High Scale Patterns 17. Part 5: Optimizing Capacities in Power BI Enterprises
18. Chapter 13: Working with Capacities 19. Chapter 14: Performance Needs for Fabric Artifacts 20. Chapter 15: Embedding in Web Apps 21. Index 22. Other Books You May Enjoy

Loading, Transforming, and Refreshing Data

So far, we have focused a lot on performance monitoring and investigation. We have now reached the next phase of our journey into Power BI performance management. Here, we will begin looking at what actions we can take to remedy the performance issues we discovered while using the tools that were introduced in previous chapters. From here on, each chapter will look deeper at a specific area with solutions and guidance.

Loading new data periodically is a critical part of any analytical system and this mainly applies to Import mode for Power BI. Data refreshes and their associated transformations can be some of the most CPU and memory-intensive operations. Reports depend on current data. Failures can cause users to not trust the report data. Large semantic models that occupy a significant portion of a host’s memory, and that have complex data transformations, are more prone to resource contention. Poorly designed transformations contribute...

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