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)

Analyzing kurtosis

Kurtosis is a measure of how the distribution of a set of data compares with a normal distribution. Specifically, kurtosis measures the tailedness of a distribution with respect to a normal bell curve. We should think of this in terms of the distribution of probability. A normal bell curve is said to be mesokurtic. Distributions that have more kurtosis than a normal bell curve are called leptokurtic. Leptokurtic distributions have wide tails, meaning that they have a wide range of outliers, with some of those outliers being extreme. Distributions with less kurtosis than a normal bell curve are called platykurtic. Platykurtic distributions are stable with a paucity of extreme outliers. Kurtosis is a useful computation for decision-making in that kurtosis directly speaks to risk. For example, investors who invest in stocks with a leptokurtic distribution are engaging...