Visual Data Storytelling with Tableau

Lindy Ryan is passionate about telling stories with data. She specializes in translating raw data into insightful stories through carefully curated visuals and engaging narrative frameworks. Before joining academia, Lindy was the Research Director for research and advisory firm Radiant Advisors from 2011 through 2016. In this role Lindy led Radiant’s analyst activities in the confluence of data discovery, visualization, and visual analytics. She also developed the methodology for the Data Visualization Competency Center (DVCC), a framework for helping data-driven organizations to effectively implement data visualization for enterprise-wide visual data analysis and communication. Her tool-agnostic approach has been successfully implemented at a variety of organizations across several industries and with multiple visualization technologies, including Tableau, Qlik, and GoodData. She remains a respected analyst in the data visualization community and is a regular contributor to several industry publications as well as a speaker at conferences worldwide. Lindy began her academic career as an associate faculty member at City University of Seattle’s School of Applied Leadership where she taught graduate courses in business leadership from 2012 to 2016. In early 2016 she joined the ambitious team at the Rutgers Discovery Informatics Institute and began contributing to multidisciplinary research focused on designing solutions for the next generation of supercomputers tasked with enabling cutting-edge extreme-scale science. Currently, Lindy leads RDI2’s research on understanding and preventing cyberbullying behaviors in emerging technology users through advanced computing approaches. Today, Lindy teaches courses in visual analytics and data visualization in Rutgers University’s Professional Science Masters program and in Montclair State University’s Business Analytics program. She is a recipient of the MSU Professing Excellence Award, which recognizes professors’ teaching excellence, particularly those who inspire and motivate students. This honor is especially meaningful to Lindy because in addition to her passion for teaching, her research includes a commitment to STEM advocacy, and she spends time on research related to increasing gender equity in CS&E and finding new and novel ways to nurture visual data literacy skills in early STEM learners. Lindy is an active committee member of the New Jersey Big Data Alliance, a partnership of New Jersey-based academic institutions that serves as the State’s legislated consortium on research, education and outreach in advanced computation and big data. She is the author of The Visual Imperative: Creating a Culture of Visual Discovery released by Morgan Kaufmann in 2016, and the owner of Black Spot Books, a traditional, analytics-driven small-press publishing house. Learn more about Lindy at www.visualdatastorytelling.com. You can also follow her on Twitter @lindy_ryan or view samples of her work on her Tableau Public page at https:// public.tableau.com/profile/lindyryan#!/.

• Foreword     xiiPreface     xiiiAcknowledgments     xxivAbout the Author     xxvi Chapter 1  Storytelling in a Digital Era     1 A Visual Revolution     2 From Visualization to Visual Data Storytelling: An Evolution     6 From Visual to Story: Bridging the Gap     8 Summary     13 Chapter 2  The Power of Visual Data Stories     15 The Science of Storytelling     16 The Brain on Stories     16 The Human on Stories     18 The Power of Stories     20 The Classic Visualization Example     20 Using Small Personal Data for Big Stories     23 The Two-or-Four Season Debate     27 Napoleon’s March     29 Stories Outside of the Box     31 Summary     32 Chapter 3  Getting Started with Tableau     33 Using Tableau     34 Why Tableau?     34 The Tableau Product Portfolio     36 Tableau Server     37 Tableau Desktop     37 Tableau Online     37 Tableau Public     37 Getting Started     38 Connecting to Data     38 Connecting to Tables     39 Live Versus Extract     41 Connecting to Multiple Tables with Joins     42 Basic Data Prep with Data Interpreter     44 Navigating the Tableau Interface     45 Menus and Toolbar     46 Data Window     47 Shelves and Cards     47 Legends     47 Understanding Dimensions and Measures     48 Dimensions     48 Measures     48 Continuous and Discrete     48 Summary     49 Chapter 4  Importance of Context in Storytelling     51 Context in Action     53 Harry Potter: Hero or Menace?     53 Ensuring Relevant Context     55 Exploratory versus Explanatory Analysis     56 Structuring Stories     58 Story Plot     59 Story Genre     60 Audience Analysis for Storytelling     61 Who     61 What     62 Why     62 How     63 Summary     64 Chapter 5  Choosing the Right Visual     65 The Bar Chart     66 Tableau How-To: Bar Chart     68 The Line Chart     70 Tableau How-To: Line Chart     72 The Pie and Donut Charts     73 Tableau How-To: Pie and Donut Charts     74 The Scatter Plot     78 Tableau How-To: Scatter Plots     79 The Packed Bubble Chart     83 Tableau How-To: Packed Bubble Charts     83 The Treemap     85 Tableau How-To: Treemaps     86 The Heat Map     88 Tableau How-To: Heat Maps     89 Maps     91 Connecting to Geographic Data     92 Assigning Geographic Roles     93 Creating Geographic Hierarchies     95 Proportional Symbol Maps     97 Choropleth Map     100 Summary     106 Chapter 6  Curating Visuals for Your Audience     107 Visual Design Building Blocks     110 Color     110 Stepped Color     114 Reversed Color     115 Color Effects     118 Opacity     118 Mark Borders     119 Mark Halos     120 The Truth about Red and Green     121 Lines     124 Formatting Grid Lines, Zero Lines, and Drop Lines     128 Formatting Borders     131 Formatting, Shading, and Banding     134 Shapes     139 Shape Marks Card     139 Custom Shapes     140 Summary     142 Chapter 7  Preparing Data for Storytelling     143 Basic Data Prep in Tableau: Data Interpreter     144 Data Interpreter in Action     145 Handling Nulls in Tableau     147 Cleaning Messy Survey Data in Excel     148 Step 1: Surface Cleaning     150 Step 2: Creating a Numeric Copy     151 Step 3: Creating the Meta Helper File     153 Pivoting Data from Wide to Tall     155 Reshaping Survey Data with Tableau 10     156 Step 1: Creating Extracts     156 Step 2: Joining Data Sources     160 Summary     165 Chapter 8  Storyboarding Frame by Frame     167 Understanding Stories in Tableau     168 Individual Visualizations (Sheets)     169 Dashboards     169 Story Points     172 The Storyboarding Process     176 Planning Your Story’s Purpose     176 Storyboarding Your Data Story     177 Building a Story     178 Making Meta Meaningful     179 Visualizing Survey Demographics     179 Act One: Demographic Dashboard and Key Question     185 Act Two: Questioning Character Aggression     187 Act Three: The Reveal     188 Summary     190 Chapter 9  Advanced Storytelling Charts     191 Timelines     192 Bar-in-Bar Charts     199 Likert Visualizations     202 100% Stacked Bar Chart     203 Divergent Stacked Bar Chart     205 Lollipop Charts     215 Labeled Lollipops     219 Word Clouds     221 Summary     224 Chapter 10  Closing Thoughts     225 Five Steps to Visual Data Storytelling     226 Step 1 Find Data That Supports Your Story     226 Step 2 Layer Information for Understanding     227 Step 3 Design to Reveal     227 Step 4 Beware the False Reveal     227 Step 5 Tell It Fast     228 The Important Role of Feedback     228 Ongoing Learning     229 Teach Yourself: External Resources     229 Companion Materials to This Text     231 Index     233