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Mastering Microsoft Power BI – Second Edition

You're reading from   Mastering Microsoft Power BI – Second Edition Expert techniques to create interactive insights for effective data analytics and business intelligence

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Product type Paperback
Published in Jun 2022
Publisher Packt
ISBN-13 9781801811484
Length 712 pages
Edition 2nd Edition
Languages
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Authors (2):
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Greg Deckler Greg Deckler
Author Profile Icon Greg Deckler
Greg Deckler
Brett Powell Brett Powell
Author Profile Icon Brett Powell
Brett Powell
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Table of Contents (18) Chapters Close

Preface 1. Planning Power BI Projects FREE CHAPTER 2. Preparing Data Sources 3. Connecting to Sources and Transforming Data with M 4. Designing Import, DirectQuery, and Composite Data Models 5. Developing DAX Measures and Security Roles 6. Planning Power BI Reports 7. Creating and Formatting Visualizations 8. Applying Advanced Analytics 9. Designing Dashboards 10. Managing Workspaces and Content 11. Managing the On-Premises Data Gateway 12. Deploying Paginated Reports 13. Creating Power BI Apps and Content Distribution 14. Administering Power BI for an Organization 15. Building Enterprise BI with Power BI Premium 16. Other Books You May Enjoy
17. Index

Relationships

Relationships play a central role in the analytical behavior and performance of the dataset. Based on the filters applied at the report layer and the DAX expressions contained in the measures, relationships determine the set of active rows for each table of the model that must be evaluated. Therefore, it’s critical that dataset designers understand how relationships drive report behavior via cross-filtering and the rules that relationships in Power BI must adhere to, such as uniqueness and non ambiguity, as discussed in the next section.

Uniqueness

Relationships in Power BI data models are always defined between single columns in two separate tables. While Power BI does support direct many-to-many relationships, it is recommended that relationships with a cardinality of many-to-many be avoided because this implies that the related columns both contain duplicate values for the related columns. Relationships based on columns containing duplicate values...

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