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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
Languages
Tools
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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

Introduction

Typically, the first step when analyzing data is to start with some questions or goals. It could be as simple as determining your most profitable customers, or more complicated, such as investigating which products are leading to losses despite high sales. After deciding on questions or goals, you would audit your data. This means identifying where data resides—whether the required fields are stored in a single or in multiple data sources and whether all fields are readily available for use. Then, you would check the integrity and validity of your data. This means checking whether the data needs any modifications in terms of cleaning, combining, or restructuring.

Once data is audited, the tools in Tableau Desktop allow you to explore it visually for more streamlined analysis. This can mean building charts, adding interactivity, separating data into groups, or creating calculations to derive more meaningful insights. Once analysis is complete, the insights you...

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