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Mastering Tableau

You're reading from   Mastering Tableau Smart Business Intelligence techniques to get maximum insights from your data

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Product type Paperback
Published in Dec 2016
Publisher Packt
ISBN-13 9781784397692
Length 476 pages
Edition 1st Edition
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Authors (2):
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Jen Stirrup Jen Stirrup
Author Profile Icon Jen Stirrup
Jen Stirrup
David Baldwin David Baldwin
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David Baldwin
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Table of Contents (14) Chapters Close

Preface 1. Getting Up to Speed – a Review of the Basics FREE CHAPTER 2. All about Data – Getting Your Data Ready 3. All about Data – Joins, Blends, and Data Structures 4. All about Data – Data Densification, Cubes, and Big Data 5. Table Calculations 6. Level of Detail Calculations 7. Beyond the Basic Chart Types 8. Mapping 9. Tableau for Presentations 10. Visualization Best Practices and Dashboard Design 11. Improving Performance 12. Interacting with Tableau Server 13. R Integration

Data blending

In a nutshell, data blending allows you to merge multiple, disparate data sources in a single view. Understanding the four following points will give you a basic grasp of data blending:

  • Data blending is typically used to merge data from multiple data sources:
    • Although as of Tableau 10, joining is possible between multiple data sources, there are still cases where data blending is the only possible option to merge data from two or more sources. The following Pants & Shirts example demonstrates such a case.

  • Data blending requires a shared dimension:
    • A date dimension is often a good candidate for blending multiple data sources.

  • Data blending aggregates and then matches. Joining matches and then aggregates:
    • This point will be covered in detail in the following section

  • Data blending does not enable dimensions from a secondary data source:
    • Attempting to use dimensions from a secondary data source will result in a * or null in the view. There is an exception to this rule, which we...
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