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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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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 10: Data Modeling and Row-Level Security

In the previous chapter, we looked at the visual layer in Power BI, where a key point was to reduce the load on data sources by minimizing the complexity and number of queries. We learned that this area is usually the easiest and quickest place to apply performance-related fixes. However, experience working with a wide range of Power BI solutions has shown that issues with the underlying dataset are very common and typically have a greater negative performance impact. Importantly, this impact can be amplified because a dataset can be used by more than one report. Dataset reuse is a recommended practice to reduce data duplication and development effort.

Therefore, in this chapter, we will move one layer deeper, into modeling Power BI datasets with a focus on Import mode. Dataset design is arguably the most critical piece, being at the core of a Power BI solution and heavily influencing usability and performance. Power BI's feature...

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