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Expert Data Modeling with Power BI

You're reading from   Expert Data Modeling with Power BI Get the best out of Power BI by building optimized data models for reporting and business needs

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Product type Paperback
Published in Jun 2021
Publisher Packt
ISBN-13 9781800205697
Length 612 pages
Edition 1st Edition
Languages
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Author (1):
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Soheil Bakhshi Soheil Bakhshi
Author Profile Icon Soheil Bakhshi
Soheil Bakhshi
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Table of Contents (18) Chapters Close

Preface 1. Section 1: Data Modeling in Power BI
2. Chapter 1: Introduction to Data Modeling in Power BI FREE CHAPTER 3. Chapter 2: Data Analysis eXpressions and Data Modeling 4. Section 2: Data Preparation in Query Editor
5. Chapter 3: Data Preparation in Power Query Editor 6. Chapter 4: Getting Data from Various Sources 7. Chapter 5: Common Data Preparation Steps 8. Chapter 6: Star Schema Preparation in Power Query Editor 9. Chapter 7: Data Preparation Common Best Practices 10. Section 3: Data Modeling
11. Chapter 8: Data Modeling Components 12. Chapter 9: Star Schema and Data Modeling Common Best Practices 13. Section 4: Advanced Data Modeling
14. Chapter 10: Advanced Data Modeling Techniques 15. Chapter 11: Row-Level Security 16. Chapter 12: Extra Options and Features Available for Data Modeling 17. Other Books You May Enjoy

Section 2: Data Preparation in Query Editor

In this section, you will learn how to prepare efficient data models in Query Editor. This chapter is all about transitioning from theory to reality. This chapter explains one of the most important aspects of data modeling, which is data preparation. Not everyone has the luxury of having a pre-built data warehouse; therefore, it is important to know how to build dimensions and facts in Query Editor. Power BI leverages the power of Power Query in Query Editor, so this chapter quickly introduces the Power Query language from a data modeling perspective then explains how to make all components needed in the star schema available to then be used in the data model layer in Power BI. We explain different techniques in data modeling along with real-world hands-on scenarios.  We also discuss common pitfalls that can easily turn building a simple report into a nightmare and ways to avoid falling into those traps.

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