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Microsoft Power BI Performance Best Practices

You're reading from   Microsoft Power BI Performance Best Practices Learn practical techniques for building high-speed Power BI solutions

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Product type Paperback
Published in Aug 2024
Publisher Packt
ISBN-13 9781835082256
Length 346 pages
Edition 2nd Edition
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Authors (2):
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Thomas LeBlanc Thomas LeBlanc
Author Profile Icon Thomas LeBlanc
Thomas LeBlanc
Bhavik Merchant Bhavik Merchant
Author Profile Icon Bhavik Merchant
Bhavik Merchant
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Toc

Table of Contents (23) Chapters Close

Preface 1. Part 1: Architecture, Bottlenecks, and Performance Targets FREE CHAPTER
2. Chapter 1: Setting Targets and Identifying Problem Areas 3. Chapter 2: Exploring Power BI Architecture and Configuration 4. Chapter 3: Learning the Tools for Performance Tuning 5. Part 2: Performance Analysis, Improvement, and Management
6. Chapter 4: Analyzing Logs and Metrics 7. Chapter 5: Optimization for Storage Modes 8. Chapter 6: Third-Party Utilities 9. Chapter 7: Performance Governance 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 Semantic Models
14. Chapter 10: Dimensional Modeling and Row Level Security 15. Chapter 11: Improving DAX 16. Chapter 12: High Scale Patterns 17. Part 5: Optimizing Capacities in Power BI Enterprises
18. Chapter 13: Working with Capacities 19. Chapter 14: Performance Needs for Fabric Artifacts 20. Chapter 15: Embedding in Web Apps 21. Index 22. Other Books You May Enjoy

Refreshing incrementally

For data sources that support queries being pushed down, Power Query can use incremental refresh. This is used mostly on fact tables that have a column to indicate the date/time the rows were updated, and there are no changes to historical data – minimum updates to rows. This useful design pattern is considered for improving refresh speeds on large data imports. By default, Power BI requires a full load of all tables when a semantic model is using Import mode. This means all the existing data in the table is discarded before the refresh operation, and it ensures that the latest data is loaded into the semantic model.

However, this results in unchanged historical data being loaded into the semantic model each time it is refreshed. If you know that you have source data that is only ever appended and historical records are never modified, you can configure individual tables to use incremental refresh to load just the most recent data. The following steps...

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