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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
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Greg Deckler
Brett Powell Brett Powell
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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

Dimension metrics

The majority of DAX measures apply aggregating functions to numeric columns of fact tables. However, several of the most important metrics of a dataset are those that focus on dimension tables, such as the count of customers who’ve purchased and those who haven’t.

It can also be necessary to count the distinct values of a dimension column such as the number of postal codes sold to or the number of distinct marketing promotions over a period of time.

In the dataset for this project, the customer dimension table is exclusive to the Internet Sales fact table, and the measure should only count customers with internet sales history.

Additionally, slowly changing dimension logic has been implemented so that a single customer defined by the CustomerAlternateKey column could have multiple rows defined by the CustomerKey column.

The following two DAX measures count the number of unique customers and products with internet sales history:

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