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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

Inventory forecasting

You have now seen some examples of inventory calculations. In some way, the measures describe a static view of inventory: the quantities at a specific point in time, and the differences compared to a fixed inventory target level. In reality, inventory is constantly in flux: products are shipped from our warehouses, and new products come in from manufacturing. It is therefore more interesting to take turnover speed into account when we analyze inventory. And as the real business value comes from balancing our inventory levels as exactly as possible with our sales, we want to have some way of looking into the future of our inventory. In other words, what we want is an inventory forecast.

Two types of forecast

There are, of course, many ways to get a prediction of the future state of inventory. We will cover two options here: first, using a sales forecast that is provided by salespeople, and second, extrapolating changes in the inventory that have occurred...

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