Book Image

DAX Cookbook

By : Greg Deckler
Book Image

DAX Cookbook

By: Greg Deckler

Overview of this book

DAX provides an extra edge by extracting key information from the data that is already present in your model. Filled with examples of practical, real-world calculations geared toward business metrics and key performance indicators, this cookbook features solutions that you can apply for your own business analysis needs. You'll learn to write various DAX expressions and functions to understand how DAX queries work. The book also covers sections on dates, time, and duration to help you deal with working days, time zones, and shifts. You'll then discover how to manipulate text and numbers to create dynamic titles and ranks, and deal with measure totals. Later, you'll explore common business metrics for finance, customers, employees, and projects. The book will also show you how to implement common industry metrics such as days of supply, mean time between failure, order cycle time and overall equipment effectiveness. In the concluding chapters, you'll learn to apply statistical formulas for covariance, kurtosis, and skewness. Finally, you'll explore advanced DAX patterns for interpolation, inverse aggregators, inverse slicers, and even forecasting with a deseasonalized correlation coefficient. By the end of this book, you'll have the skills you need to use DAX's functionality and flexibility in business intelligence and data analytics.
Table of Contents (15 chapters)

Optimizing the data model

The underlying data model used for DAX is the in-memory tabular cube. Since this data model is designed to be used in memory, the overall size of the data model is an important performance consideration since, after all, computers only have a finite amount of memory. Understanding the underlying workings of the tabular data model is imperative to building efficient data models that fit into available memory and optimize the speed and performance of DAX calculations. This recipe provides guidance on how to optimize your data model for peak efficiency.

Getting ready

To prepare for this recipe, perform the following steps:

  1. Open Power BI Desktop.
  2. Create a new file using File and then New from the ribbon...