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Expert Data Modeling with Power BI, Second Edition

You're reading from   Expert Data Modeling with Power BI, Second Edition Enrich and optimize your data models to get the best out of Power BI for reporting and business needs

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Product type Paperback
Published in Apr 2023
Publisher Packt
ISBN-13 9781803246246
Length 698 pages
Edition 2nd 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 (22) Chapters Close

Preface 1. Section I: Data Modeling in Power BI
2. Introduction to Data Modeling in Power BI FREE CHAPTER 3. Data Analysis eXpressions and Data Modeling 4. Section II: Data Preparation in Query Editor
5. Data Preparation in Power Query Editor 6. Getting Data from Various Sources 7. Common Data Preparation Steps 8. Star Schema Preparation in Power Query Editor 9. Data Preparation Common Best Practices 10. Section III: Data Modeling
11. Data Modeling Components 12. Star Schema and Data Modeling Common Best Practices 13. Section IV: Advanced Data Modeling
14. Advanced Data Modeling Techniques 15. Row-Level and Object-Level Security 16. Dealing with More Advanced Data Warehousing Concepts in Power BI 17. Introduction to Dataflows 18. DirectQuery Connections to Power BI Datasets and Analysis Services in Composite Models 19. New Options, Features, and DAX Functions 20. Other Books You May Enjoy
21. Index

Using configuration tables

In many cases, a business wants to analyze some of the business metrics in clusters. Some good examples are analyzing sales by unit price range, analyzing sales by product cost range, analyzing customers by their age range, or analyzing customers by commute distance. In all of these examples, the business does not need to analyze constant values; instead, it is more about analyzing a metric (sales, in the preceding examples) by a range of values.

Some other cases are related to data visualization, such as dynamically changing the color of values when they are in a specific range. An example is to change the values’ color to red in all visuals analyzing sales if the sales value for the data points is less than the average sales over time. This is a relatively advanced analysis that can be reused in our reports to keep visualizations’ color consistent.

In the preceding examples, we need to define configuration tables. In the latter example...

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