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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

Modeling the QuantoBikes sales process

Many business systems record different stages in a business process. A typical enterprise resource planning (ERP) system allows us to define the stages, for an invoice to be sent, for example. It is important to note that recording these stages assumes that a business process works in that specific way. The reality is almost always different.

In fact, analyzing the difference between a designed process and the actual process is a field of its own, named process mining. When you consider a large number of invoices, you will commonly find many deviations from the process as it is designed. Optimizing the business process starts with knowing which variants of the process occur. Some odd variants may have a large impact on throughput or even profitability; eliminating these variants by specific corrective actions can significantly improve business process performance. Analysts who apply process mining can also apply machine learning to predict...

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