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DAX Cookbook

You're reading from   DAX Cookbook Over 120 recipes to enhance your business with analytics, reporting, and business intelligence

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Product type Paperback
Published in Mar 2020
Publisher Packt
ISBN-13 9781839217074
Length 552 pages
Edition 1st Edition
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Author (1):
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Greg Deckler Greg Deckler
Author Profile Icon Greg Deckler
Greg Deckler
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Table of Contents (15) Chapters Close

Preface 1. Thinking in DAX 2. Dealing with Dates and Calendars FREE CHAPTER 3. Tangling with Time and Duration 4. Transforming Text and Numbers 5. Figuring Financial Rates and Revenues 6. Computing Customer KPIs 7. Evaluating Employment Measures 8. Processing Project Performance 9. Calculating Common Industry Metrics 10. Using Uncommon DAX Patterns 11. Solving Statistical and Mathematical Formulas 12. Applying Advanced DAX Patterns 13. Debugging and Optimizing DAX 14. Other Books You May Enjoy

Forecasting with a de-seasonalized correlation coefficient

Calculating correlation coefficients is a method of determining whether or not two sets of data are related to one another. In addition, correlation coefficients can tell you whether the datasets are positively or negatively (inversely) related. Positive relationships exist when the values in the data change in the same direction, either going down or up at the same time. Inverse relationships exist when values in the datasets go up and down contrary to one another. Both positively and inversely related datasets can be useful forecasting indicators as long as the correlation coefficient between the two datasets is strong. If we know that two datasets are related, then we can potentially use the known values in one dataset to estimate the unknown values in the other dataset.

A typical formula for calculating a correlation...

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