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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

Configuring for faster DirectQuery

There are a few settings that can be adjusted in Power BI to speed up DirectQuery datasets. We will explore these next.

Power BI Desktop settings

In the Power BI Desktop options, there is a section called Published dataset settings (as shown in Figure 3.6). The highlighted area shows the setting that controls how many connections per data source can be made in parallel. The default is 10. This means no matter how many visuals are in a report, or how many users are accessing the report in parallel, only 10 connections at a time will be made.

If the data source can handle more parallelism, it is recommended to increase this value before publishing the dataset to the Power BI service. However, with very busy data sources, you may find overall performance can improve by reducing the value instead. This is because too many parallel queries can overwhelm the source and result in a longer total execution time. A lower value means some queries will...

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