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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

Understanding Tableau's data-handling engine

Tableau's data-handling engine is usually not well comprehended by even advanced authors because it's not an overt part of day-to-day activities; however, for the author who wants to truly grasp how to ready data for Tableau, this understanding is indispensable. In this section, we will explore Tableau's data-handling engine and how it enables structured yet organic data mining processes in the enterprise.

To begin, let's clarify a term. The phrase Data-Handling Engine (DHE) in this context references how Tableau interfaces with and processes data. This interfacing and processing is comprised of three major parts: Connection, Metadata, and VizQL. Each part is described in detail in the following section. In other publications, Tableau's DHE may be referred to as a metadata model or the Tableau infrastructure. I've elected not to use either term because each is frequently defined differently in different contexts...

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