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)

Handling errors with ERROR, ISERROR, and IFERROR

As with any programming language, coding DAX calculations will inevitably result in an error being generated. While error handling in DAX is perhaps not quite as mature and robust as some other programming languages, DAX does provide some basic capabilities for handling errors within DAX code. This recipe demonstrates how to use three special DAX functions, ERROR, ISERROR, and IFERROR, in order to perform basic error checking within DAX calculations.

Getting ready

To prepare for this recipe, perform the following steps:

  1. Open Power BI Desktop.
  2. Use an Enter Data query to create a table called R01_Table with the following data:

Color

Value

Red

0

Green

1

...