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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
Languages
Tools
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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

Building efficient models

We will begin with some theoretical concepts on how to model data for efficient storage, which leads to faster queries. These design techniques have been around the data warehouse world since the 1990s. The simplicity of dimensional modeling has always been centered around efficient structures for analytical reports. The Analysis Services engine was designed for star schemas in both the multidimensional cubes as well as tabular semantic models.

Let’s review together the basics of dimensional modeling.

The Kimball dimensional model theory

Data modeling can be thought of as how to group and connect attributes in a set of data. There are competing schools of thought as to what style of data modeling is the best and they are not always mutually exclusive. Learning about dimensional modeling is the best fit for Power BI semantic models, so we will concentrate on this method.

We will be looking at dimensional modeling, a very popular technique...

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