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Extreme DAX

Extreme DAX

By : Michiel Rozema, Henk Vlootman
4.9 (44)
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Extreme DAX

Extreme DAX

4.9 (44)
By: Michiel Rozema, Henk Vlootman

Overview of this book

This book helps business analysts generate powerful and sophisticated analyses from their data using DAX and get the most out of Microsoft Business Intelligence tools. Extreme DAX will first teach you the principles of business intelligence, good model design, and how DAX fits into it all. Then, you’ll launch into detailed examples of DAX in real-world business scenarios such as inventory calculations, forecasting, intercompany business, and data security. At each step, senior DAX experts will walk you through the subtleties involved in working with Power BI models and common mistakes to look out for as you build advanced data aggregations. You’ll deepen your understanding of DAX functions, filters, and measures, and how and when they can be used to derive effective insights. You’ll also be provided with PBIX files for each chapter, so that you can follow along and explore in your own time.
Table of Contents (17 chapters)
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Free Chapter
1
Part I: Introduction
6
Part II: Business cases
15
Other Books You May Enjoy
16
Index

Best practices in DAX

When working with DAX, you will benefit from following some best practices. Applying these will help you create fast models, make it easier to maintain your models in the long term, and allow you to better support others who create Power BI reports or other output from your models.

Think in terms of DAX measures primarily

If we did not make ourselves clear enough above: your main DAX tool should be DAX measures. These are highly dynamic, do not make the model larger, and there is no calculation you cannot do through a measure.

As a rule of thumb, calculated columns and calculated tables are a no-go, until you have very good arguments for using them!

Build explicit measures

We recommend creating explicit DAX measures instead of using numeric columns from (fact) tables directly in visual reports. There are several reasons for this:

  • A measure is created by the Power BI model anyway when you use a column in a report, and it is easy...

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