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)

Building a revenue growth rate

How fast a company is growing or shrinking is a critical factor in any business analysis. The revenue growth rate is a direct way of measuring growth based on the revenue generated by the sale of goods and services. The revenue growth rate compares the revenue generated by business between two equal-length periods, such as this year and the previous year, this quarter and the previous quarter, or this month and the previous month.

This recipe demonstrates how to create a revenue growth rate metric and display this metric in a visualization.

Getting ready

To prepare for this recipe, do the following:

  1. Open Power BI Desktop.
  2. Use an Enter Data query to create a table called R02_Table that contains...