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Mastering Tableau 2021

You're reading from   Mastering Tableau 2021 Implement advanced business intelligence techniques and analytics with Tableau

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Product type Paperback
Published in May 2021
Publisher Packt
ISBN-13 9781800561649
Length 792 pages
Edition 3rd Edition
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Authors (2):
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David Baldwin David Baldwin
Author Profile Icon David Baldwin
David Baldwin
Marleen Meier Marleen Meier
Author Profile Icon Marleen Meier
Marleen Meier
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Toc

Table of Contents (18) Chapters Close

Preface 1. Getting Up to Speed – A Review of the Basics 2. All About Data – Getting Your Data Ready FREE CHAPTER 3. Tableau Prep Builder 4. All About Data – Joins, Blends, and Data Structures 5. Table Calculations 6. All About Data – Data Densification, Cubes, and Big Data 7. Level of Detail Calculations 8. Beyond the Basic Chart Types 9. Mapping 10. Tableau for Presentations 11. Visualization Best Practices and Dashboard Design 12. Advanced Analytics 13. Improving Performance 14. Interacting with Tableau Server/Online 15. Programming Tool Integration 16. Another Book You May Enjoy
17. Index

Level of Detail Calculations

When we talk about Level of Detail (LOD) calculations in Tableau, we mean three expressions: FIXED, INCLUDE, and EXCLUDE. These three expressions open a world of options by providing the ability to create calculations that target specific levels of granularity. In older versions of Tableau, data granularity for a worksheet was established by the dimensions in a view. If the view contained dimensions for, for example, Region, State, and Postal Code, but the author wanted to create a City-level calculation, the City dimension would need to be included on the view. Furthermore, there was no mechanism for excluding or ignoring a given dimension on a view. Admittedly, the desired results could normally be obtained through some complex and sometimes convoluted use of table calculations, data blends, and so on. Fortunately, LOD calculations greatly simplify these use case scenarios and, in some cases, enable what was previously impossible.

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