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     xii
Preface     xiii
Acknowledgments     xxiv
About 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