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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 8: Loading, Transforming, and Refreshing Data

So far, we have focused a lot on performance monitoring and investigation. We have now reached the next phase of our journey into Power BI performance management. Here, we will begin looking at what actions we can take to remedy the performance issues we discovered while using the tools that were introduced in previous chapters. From here on, each chapter will look deep at a specific area of a Power BI solution and will provide performance guidance. The first of these is loading data into Power BI.

Loading new data periodically is a critical part of any analytical system, and in Power BI, this applies to Import mode datasets. Data refresh and its associated transformations can be some of the most CPU and memory-intensive operations. This can affect user activities and cause refresh failures. Large datasets that occupy a significant portion of a host's memory, and that have complex data transformations, are more prone to...

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