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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

Optimizing dataflows

A Power BI Dataflow is a type of artifact contained within a Power BI workspace. A dataflow contains Power Query data transformation logic, which is also defined in the M query language that we introduced earlier. The dataflow contains the definition of one or more tables produced by those data transformations. Once it has been successfully refreshed, the dataflow also contains a copy of the transformed data stored in Azure Data Lake.

A dataflow might seem very similar to the query objects you define in Power BI Desktop, and this is true. However, there are some important differences, as noted in the following points:

  • A dataflow can only be created online through the Power BI web application via Power Query Online.
  • A dataflow is a standalone artifact that can exist independently. It is not bundled or published with a dataset, but dataset items can use the dataflow as a standard data source.
  • There are some UI and functionality differences between...
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