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)

Determining the required sample size

Sample size is an important concept in statistics. In order to make reliable inferences of a population based upon a sample of that population, it is necessary to have a statistically significant sample size. One method of calculating the required sample size is Cochran's formula, named after the statistician William Gemmell Cochran.

Cochran's formula is as follows:

Here, p is the expected percent of the population with the desired attribute. e is the desired precision or margin of error. Z is something called the z-score, which is found in a z-score table (it's a statistics thing). In order to find the z-score, we must choose a desired confidence value (how confident are we in the results).

This recipe implements Cochran's formula for determining sample size in DAX based upon the chosen confidence levels, the proportion...