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Microsoft Power BI Performance Best Practices

You're reading from   Microsoft Power BI Performance Best Practices A comprehensive guide to building consistently fast Power BI solutions

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Product type Paperback
Published in Apr 2022
Publisher Packt
ISBN-13 9781801076449
Length 312 pages
Edition 1st Edition
Languages
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Author (1):
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Bhavik Merchant Bhavik Merchant
Author Profile Icon Bhavik Merchant
Bhavik Merchant
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Toc

Table of Contents (21) 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: DirectQuery Optimization 5. Part 2: Performance Analysis, Improvement, and Management
6. Chapter 4: Analyzing Logs and Metrics 7. Chapter 5: Desktop Performance Analyzer 8. Chapter 6: Third-Party Utilities 9. Chapter 7: Governing with a Performance 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 Datasets
14. Chapter 10: Data Modeling and Row-Level Security 15. Chapter 11: Improving DAX 16. Chapter 12: High-Scale Patterns 17. Part 5: Optimizing Premium and Embedded Capacities
18. Chapter 13: Optimizing Premium and Embedded Capacities 19. Chapter 14: Embedding in Applications 20. Other Books You May Enjoy

Chapter 13: Optimizing Premium and Embedded Capacities

In the previous chapter, we looked at ways to deal with high data and user scale. The first option we provided was to leverage Power BI Premium because it has higher dataset size limits than Power BI's shared capacity.

In this chapter, we will take a much closer look at the Premium (P and EM) and Embedded (A) capacities. Even though they are purchased and billed differently, with a couple of minor exceptions, they offer the same services on similar hardware and benefit from the same optimization guidance. Therefore, we will continue to refer to just the Premium capacity for the remainder of this chapter and will call out Embedded only if there is a material difference. We will treat the Premium Per User (PPU) licensing model the same way.

We will learn how there is more to differentiate Premium than just the increased dataset limits. This is because the Premium capacity offers unique services and advanced features...

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