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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

General data transformation guidance

Power Query allows users to build relatively complex data transformation pipelines through a point and click interface. Each step of the query is defined by a line of M script that has been autogenerated by the UI. It's quite easy to load data from multiple sources and perform a wide range of transformations in a somewhat arbitrary order. Suboptimal step ordering and configuration can use unnecessary resources and slow down the data refresh. Sometimes, the problem might not be apparent in Power BI Desktop. This is more likely when using smaller subsets of data for development, which is a common practice. Hence, it's important to apply good Power Query design practices to avoid surprises. Let's begin by looking at how Power Query uses resources.

Data refresh, parallelism, and resource usage

When you perform a data refresh for an Import mode dataset in the Power BI service, the dataset stays online. It can still be queried by...

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