Pro Tableau (Seema Acharya Subhashini Chellappan) (Z-Library)

Seema Acharya and Subhashini Chellappan Pro Tableau A Step-by-Step Guide

Seema Acharya Pune, Maharashtra, India Subhashini Chellappan Bangalore, Karnataka, India Any source code or other supplementary materials referenced by the author in this text are available to readers at www.apress.com . For detailed information about how to locate your book’s source code, go to www.apress.com/source-code/ . Readers can also access source code at SpringerLink in the Supplementary material section for each chapter. ISBN 978-1-4842-2351-2 e-ISBN 978-1-4842-2352-9 DOI 10.1007/978-1-4842-2352-9 Library of Congress Control Number: 2016961342 © Seema Acharya and Subhashini Chellappan 2017 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. Trademarked names, logos, and images may appear in this book. Rather than use a trademark symbol with every occurrence of a trademarked name, logo, or image we use the names, logos, and images only in an editorial fashion and to the benefit of the trademark owner, with no intention of infringement of the trademark. The use in this publication of trade names, trademarks, service marks, and similar terms, even if they are not identified as such, is not to be taken as an expression of opinion as to whether or not they are subject to proprietary rights.

While the advice and information in this book are believed to be true and accurate at the date of publication, neither the authors nor the editors nor the publisher can accept any legal responsibility for any errors or omissions that may be made. The publisher makes no warranty, express or implied, with respect to the material contained herein. Printed on acid-free paper Distributed to the book trade worldwide by Springer Science+Business Media New York, 233 Spring Street, 6th Floor, New York, NY 10013. Phone 1-800-SPRINGER, fax (201) 348-4505, e-mail orders-ny@springer- sbm.com, or visit www.springeronline.com. Apress Media, LLC is a California LLC and the sole member (owner) is Springer Science + Business Media Finance, Inc. (SSBM Finance, Inc.). SSBM Finance, Inc. is a Delaware corporation.

About the Technical Reviewer I am Rajeev, an author, blogger, a Tableau lover, data evangelist from Hyderabad, India. Working for Deloitte, I am a multidisciplinary designer working in data visualization, interaction design and innovation. With expertise in developing Tableau, Web-focus-based visualization and reporting applications, I love creativity and enjoy experimenting with various technologies. I am a very individualistic person who has a gift for figuring out how people who are different can work together productively. In addition, because I am driven by talent, I can constantly investigate the “hows”, and “whys” of a given situation which would be very beneficial to not only myself, but also for other people. Follow me on LinkedIn: https://in.linkedin.com/in/rajvivan Twitter : @rajvivan Website : http://www.tableaulearners.com/

Introduction Why this book? Data visualization is changing the way the world looks at data. This book will help you make sense of data quickly and effectively, make you look at data differently, more imaginatively. It will help you visualize from the end users perspective. It will impel you to dig for more insights. The topics covered along with demonstrations and illustrations are certain to promote creative data exploration. The book has within its scope the following: Sourcing data into Tableau from single and multiple data sources (both homogeneous and heterogeneous) Statistical analysis in Tableau Integration of R Analytics with Tableau Concepts behind visualization and industry best practices

Who is this book for? The audience for this book includes all levels of IT professionals, executives responsible for determining IT strategies, system administrators, data analysts and decision makers responsible for driving strategic initiatives, etc. It will help to chart your journey from a novice to a professional visualization expert. The book will also make for interesting read for business users / management graduates / business analysts. How is this book organized? Our book has 11 chapters. Here is a sneak peek … Chapter 1 : This chapter explains the meaning of visualization and the role it plays in BI and data science. It covers the various visualization tools available on the market. It highlights Tableau’s products lines, such as Tableau Desktop, Tableau Server, Tableau Online, Tableau Public and Tableau Reader. It also throws light on the various file types in Tableau and brings forth the difference between saving the Tableau workbook as .twb or .twbx etc., the Tableau data source as .tds or .tdsx etc. Chapter 2 : The aim of this chapter is to outline the step-by-step process to connect Tableau to varied data sources, elucidate the concept of joins and blends, and enumerate the differences between live connection and working with data extracts. Chapter 3 : This chapter serves to aid in organizing data into groups and sets. It further delves into the difference between groups and sets. Chapter 4 : This chapter will strengthen our comprehension of measure names and measure values and the techniques to have more than one measure depicted on a single view / worksheet. Chapter 5 : This chapter clearly explains the connotation and significance of calculations, such as moving average, year-on-year growth, level of detail (LOD).These quick table calculations have been explained with the help of case scenarios. Chapter 6 : This chapter will help you customize the data using string functions such as concatenation, find, left, etc., number functions which will bring out the difference between aggregated and non-aggregated measures, date functions such as datepart, datediff, dateadd, dateparse, etc. Chapter 7 : This chapter focusses on enunciating the significance of statistics in analysis. It will elaborate the usage of reference line, constant

line, trend line, summary card, etc. Chapter 8 : This chapter will provide an easy comprehension and usage of the various chart forms such as pie chart, heat map, treemap, stacked bar chart, line graph, word cloud, etc., the concepts behind each one of them, the pros and cons, the best chart form to use in a particular scenario etc. Chapter 9 : This chapter will build on your knowledge of visualization with advanced chart forms, such as waterfall charts, bump charts and bullet graphs, a chart form that enables visualizing staged progress to your goal. Chapter 10 : This chapter is designed to help learners weave a powerful and insightful story by putting together the various reports (views / worksheets) into an interactive dashboard. Chapter 11 : This chapter talks about the steps involved in integrating R Analytics with Tableau. It introduces data mining and the implementation of data mining algorithms in R and Tableau. The source code (the .twbx for all the demos and assignments) are also shared. Feel free to download them from Apress site ( www.apress.com ) How to get the most out of this book? It is easy to leverage the book to gain the maximum by religiously abiding by the following: Read the chapters thoroughly. Get hands-on by following the step-by- step instructions stated in the demonstrations. Do NOT skip any demonstration. If need be, repeat it a second time or till the time the concept is firmly etched. Join a Tableau community or discussion forum. Read up customer stories provided on Tableau site ( www.Tableau.com ) to learn how customers the world over are enhancing their visualization experience. Read the blogs of data visualization experts, such as Stephen Few, Edward Tufte, and Hans Rosling, etc. Where next?

We have endeavored to unleash the power of Tableau as a data visualization tool and introduce you to several chart forms / visualizations. We recommend that you read the book from cover to cover, but if you are not that kind of person, we have made an attempt to keep the chapters self-contained so that you can go straight to the topics that interest you most.Whichever approach you choose, we wish you well! A quick word for fellow instructors We’ve paid extra attention in to setting the order of the chapters and to the flow of topics within each chapter. This was undertaken in this way to assist our fellow instructors and academicians in carving out a syllabus from the Table of Contents (TOC) of the book. The complete TOC can qualify as the syllabi for a semester or if the college has an existing syllabus on business intelligence or data visualization or analytics and visualization, a few chapters can be added to the syllabi to make it more robust. We leave it to your discretion on how you wish to use these resources for your students. We have ensured that each tool / component discussed in the book is with adequate hands-on content to enable you to teach better and provide ample hands-on practice to your students. Happy Learning!!! Authors: Seema Acharya Subhashini Chellappan

Acknowledgments The making of the book was a journey that we are glad we undertook. The journey spanned a few months, but the experience will last a lifetime. We had our families, friends, colleagues, and well-wishers onboard this journey, and we wish to express our deepest gratitude to each one of them. Without their unwavering support and affection, we could not have pulled it off. We are grateful to the student and teacher community who with their continual bombardment of queries impelled us to learn more, simplify our learnings and findings, and place it neatly in the book. This book is for them. We wish to thank our friends – the practitioners from the field for their good counsel – for filling us in on the latest in the field of visualization and sharing with us valuable insights on the best practices and methodologies followed therein. A special thanks to our technical reviewer for his vigilant review and the filling in with his expert opinion. We have been fortunate to have the support of our teams who sometimes knowingly and at other times unknowingly contributed to the making of the book by lending us their steady support. We consider ourselves very fortunate for the editorial assistance provided by Apress Media. We are thankful to Celestin Suresh John, senior manager, editorial acquisition, Apress and Springer Science and Business Media Company, for signing us up for this wonderful creation. We wish to acknowledge and appreciate Sanchita Mandal, coordinating editor, Laura Berendson, development editor, and their team of associates who adeptly guided us through the entire process of preparation and publication. And finally we can never amply thank our families and friends who have been our pillars of strength, our stimulus, and our soundboards all through the process, and tolerated patiently our crazy schedules as we assembled the book.

Contents Chapter 1: Introducing Visualization and Tableau 1. 1 Why data visualization? 1. 2 What can data visualization help with? 1. 3 An introduction to visualization 1. 3. 1 Which domain is leveraging the power of data visualization? 1. 3. 2 Who is using data visualization? 1. 3. 3 Top data visualization tools 1. 3. 4 History of data visualization 1. 3. 5 What are the expectations for a data visualization tool? 1. 3. 6 Let us see how Tableau fulfils the expectations 1. 3. 7 Reasons to make a switch to Tableau 1. 4 Positioning of Tableau 1. 5 Tableau product line 1. 6 File types in Tableau 1. 6. 1 Tableau Workbook (twb) 1. 6. 2 Tableau Packaged Workbook (twbx) 1. 6. 3 Tableau Data Source (tds) file 1. 6. 4 Tableau Packaged Data Source (tdsx) file

1. 6. 5 Tableau bookmark 1. 6. 6 Tableau data extract 1. 7 Points to remember 1. 8 Assignments 1. 9 Next steps Chapter 2: Working with Single and Multiple Data Sources 2. 1 Desktop architecture 2. 1. 1 Data layer 2. 1. 2 Data connectors 2. 1. 3 Live connection 2. 1. 4 In-memory 2. 2 Tableau environment 2. 2. 1 To open 2. 2. 2 To close 2. 2. 3 Start page 2. 2. 4 Data Source Page 2. 2. 5 Workspace 2. 2. 6 Workbooks and Sheets 2. 2. 7 Visual Cues and Icons in Tableau 2. 3 Connect to a File

2. 3. 1 Connect to a Text File 2. 3. 2 Connect to MS Access 2. 3. 3 Connecting to RData files 2. 4 Connect to a Server 2. 4. 1 Connecting to MS SQL Server 2014 Management Studio 2. 4. 2 Connecting to MySQL 2. 4. 3 Connecting to NoSQL Databases 2. 5 Metadata Grid 2. 6 Joins 2. 6. 1 Adding Fields to the Data Pane 2. 6. 2 Exploring different types of Join 2. 6. 3 Union 2. 7 Custom SQL 2. 7. 1 Demo 1 2. 8 Data Blending 2. 8. 1 Demo 1 2. 9 Data Extracts 2. 9. 1 Demo 1 2. 10 Points to Remember 2. 11 Next Step

Chapter 3: Simplifying and Sorting Your Data 3. 1 Filtering 3. 1. 1 Why filtering? 3. 1. 2 What is filtering? 3. 1. 3 How to apply “Filter”? 3. 2 Sorting 3. 2. 1 Why sorting? 3. 2. 2 What is sorting? 3. 2. 3 How to apply sorting? 3. 2. 4 Discrete and Continuous Dates 3. 2. 5 Why and what? 3. 3 Groups 3. 3. 1 Why groups? 3. 3. 2 What is a group? 3. 3. 3 How to create a group? 3. 3. 4 Editing an existing group 3. 3. 5 Creating Hierarchies 3. 3. 6 Sets 3. 4 Difference between a set and group 3. 4. 1 Group

3. 4. 2 Set 3. 4. 3 Creating parameters 3. 5 Points to remember 3. 6 Next step Chapter 4: Measure Names and Measure Values 4. 1 Why are measure names and measure values required? 4. 1. 1 What are measure names and measure values? 4. 1. 2 Where do these fields come from? 4. 1. 3 Measures on an independent axis 4. 1. 4 Blended axes 4. 1. 5 Dual axis 4. 2 Points to Remember 4. 3 Next steps Chapter 5: Table Calculations 5. 1 What is a table calculation? 5. 2 Running Total of Sales 5. 2. 1 Demo 1 5. 3 Profitability as Percent of Total 5. 3. 1 Demo 1 5. 4 Moving average

5. 4. 1 Where is it used? 5. 4. 2 Types of moving average 5. 4. 3 Demo 1 5. 5 Rank 5. 5. 1 Demo 1 5. 6 LOD (Level of Detail) 5. 6. 1 Demo 1 5. 6. 2 Demo 2 5. 7 Percentile 5. 7. 1 Demo 1 5. 8 Year over Year Growth 5. 8. 1 Demo 1 5. 8. 2 Demo 2 5. 8. 3 Demo 3 5. 9 Points to remember 5. 10 Next Steps Chapter 6: Customizing Data 6. 1 Number functions 6. 1. 1 CEILING(number) and FLOOR(number) 6. 1. 2 MAX(number, number), MIN(number, number)

6. 1. 3 ABS(number) 6. 2 String functions 6. 2. 1 Concatenation 6. 2. 2 Left() and Find() functions 6. 2. 3 Contains() function 6. 2. 4 Len() function 6. 3 Logical Functions 6. 3. 1 CASE 6. 3. 2 IIF() function 6. 3. 3 IF ELSE 6. 3. 4 IF ELSEIF 6. 4 Date functions 6. 4. 1 DATEDIFF() 6. 4. 2 DATEADD() function 6. 4. 3 DATENAME 6. 5 Aggregate functions 6. 5. 1 ATTR(expression) 6. 6 Table calculation functions 6. 6. 1 First(), Index() 6. 7 Points to remember

6. 8 Next steps Chapter 7: Statistics 7. 1 Why use statistics? 7. 2 What is statistics? 7. 3 Descriptive statistics 7. 4 Inferential statistics 7. 5 Few terms in statistics 7. 6 Why do we use inferential statistics? 7. 7 Why do we use descriptive statistics? 7. 7. 1 What is the measure of central tendency here? 7. 8 Five magic number summary 7. 8. 1 Mean 7. 8. 2 Median 7. 8. 3 Mode 7. 8. 4 When to use which average? 7. 9 Spread of data 7. 9. 1 Range 7. 9. 2 Interquartile range 7. 9. 3 Variance and standard deviation 7. 9. 4 Standard deviation

7. 9. 5 Assignment 1 7. 9. 6 Assignment 2 7. 10 Box plot 7. 10. 1 Plotting box and whiskers plot in Tableau 7. 11 Statistics tools in Tableau 7. 11. 1 Reference lines 7. 12 Trend lines 7. 12. 1 Answering questions with trend lines 7. 13 Forecasting 7. 13. 1 Demo 1 7. 14 Points to remember 7. 15 Next steps Chapter 8: Chart Forms 8. 1 Pie chart 8. 1. 1 What is a pie chart? 8. 1. 2 When to use a pie chart? 8. 1. 3 How to read a pie chart? 8. 1. 4 Pros 8. 1. 5 Cons 8. 1. 6 Five tips for using pie charts

8. 1. 7 A critique’s view 8. 1. 8 An alternative for a pie chart 8. 1. 9 What can further add to the woes? 8. 2 Treemaps 8. 2. 1 Pros 8. 2. 2 References 8. 3 Heat Map 8. 3. 1 Why use heat maps? 8. 3. 2 How to create a heat map? 8. 4 Highlight Table 8. 4. 1 Demo 1 8. 4. 2 Demo 2 8. 5 Line Graph 8. 5. 1 Demo 1 8. 5. 2 Demo 2 8. 6 Stacked Bar Chart 8. 6. 1 Demo 1 8. 6. 2 Steps to create a stacked bar chart 8. 7 Gantt chart 8. 7. 1 Shortcomings of Gantt charts