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The Tableau Workshop

You're reading from   The Tableau Workshop A practical guide to the art of data visualization with Tableau

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Product type Paperback
Published in Apr 2022
Publisher Packt
ISBN-13 9781800207653
Length 822 pages
Edition 1st Edition
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Authors (5):
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Shweta Savale Shweta Savale
Author Profile Icon Shweta Savale
Shweta Savale
Kenneth Michael Cherven Kenneth Michael Cherven
Author Profile Icon Kenneth Michael Cherven
Kenneth Michael Cherven
Sumit Gupta Sumit Gupta
Author Profile Icon Sumit Gupta
Sumit Gupta
Sylvester Pinto Sylvester Pinto
Author Profile Icon Sylvester Pinto
Sylvester Pinto
JC Gillet JC Gillet
Author Profile Icon JC Gillet
JC Gillet
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Table of Contents (12) Chapters Close

Preface
1. Introduction: Visual Analytics with Tableau 2. Data Preparation: Using Tableau Desktop FREE CHAPTER 3. Data Preparation: Using Tableau Prep 4. Data Exploration: Comparison and Composition 5. Data Exploration: Distributions and Relationships 6. Data Exploration: Exploring Geographical Data 7. Data Analysis: Creating and Using Calculations 8. Data Analysis: Creating and Using Table Calculations 9. Data Analysis: Creating and Using Level of Details (LOD) Calculations 10. Dashboards and Storyboards 11. Tableau Interactivity: Part 1

The Importance of Visual Analytics

As mentioned earlier, "Visual Analytics" can be defined as the process of exploring and analyzing data by visualizing it as charts and graphs. This enables end users to quickly consume the information and, in turn, empowers them to make quicker and better decisions.

In this section, you will learn why data visualization is a better tool for evaluation than looking at large volumes of data in numeric format.

All of us have at some point heard the expression "A picture is worth a thousand words." Indeed, it has been found that humans are great at identifying and recognizing patterns and trends in data when consumed as visuals as opposed to large volumes of data in tabular or spreadsheet formats.

To understand the importance and the power of data visualization/visual analytics, let's look at one of the classic examples: Anscombe's Quartet. Anscombe's quartet is comprised of four distinct datasets with nearly...

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