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)

Achieving actual cost

Actual cost, or AC, of a project is, as its name implies, the costs of delivering a project based upon the material goods that have been purchased and the costs associated with project resources. The cost of project resources is generally calculated by multiplying the hours each resource worked on a project by the hourly rate or cost of each resource. This recipe demonstrates how to calculate the actual costs of a project and its tasks using the hours each resource reported as project work and the hourly cost of those resources.

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 R04_Project that contains the following data...