DAX Cookbook

DAX Cookbook

by Greg Deckler
DAX Cookbook

DAX Cookbook

by Greg Deckler

Paperback

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Overview

Solve real-world business problems by learning how to create common industry key performance indicators and other calculations using DAX within Microsoft products such as Power BI, SQL Server, and Excel.

  • Learn to write sophisticated DAX queries to solve business intelligence and data analytics challenges
  • Handle performance issues and optimization within the data model, DAX calculations and more
  • Solve business issues with Microsoft Excel, Power BI, and SQL Server using DAX queries

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.

  • Understand how to create common calculations for dates, time, and duration
  • Create key performance indicators (KPIs) and other business calculations
  • Develop general DAX calculations that deal with text and numbers
  • Discover new ideas and time-saving techniques for better calculations and models
  • Perform advanced DAX calculations for solving statistical measures and other mathematical formulas
  • Handle errors in DAX and learn how to debug DAX calculations
  • Understand how to optimize your data models

Business users, BI developers, data analysts, and SQL users who are looking for solutions to the challenges faced while solving analytical operations using DAX techniques and patterns will find this book useful. Basic knowledge of the DAX language and Microsoft services is mandatory.


Product Details

ISBN-13: 9781839217074
Publisher: Packt Publishing
Publication date: 03/19/2020
Pages: 552
Product dimensions: 7.50(w) x 9.25(h) x 1.12(d)

About the Author

Greg Deckler is Vice President of the Microsoft Practice at Fusion Alliance and has been a professional technology systems consultant for over 25 years. Internationally recognized as an expert in Power BI, Greg Deckler is a Microsoft MVP for Data Platform and a superuser within the Power BI community with over 100,000 messages read, more than 11,000 replies, over 2,300 answers, and more than 75 entries in the Quick Measures Gallery. Greg founded the Columbus Azure ML and Power BI User Group (CAMLPUG) and presents at numerous conferences and events, including SQL Saturday, DogFood, and the Dynamic Communities User Group/Power Platform Summit.

Table of Contents

Table of Contents
  1. Thinking in DAX
  2. Dealing with Dates and Calendars
  3. Tangling with Time and Duration
  4. Transforming Text and Numbers
  5. Figuring Financial Rates and Revenues
  6. Computing Customers 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
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