level of product mastery with the real-world experience gained through developing thousands of visualizations for dozens of clients. In addition to his recognized expertise in data visualization and Tableau, Steve has decades of experience as a successful instructor in all areas of computer-based technology. Steve has taught thousands of people in both large and small organizations and is known for conducting his seminars with clarity, patience, and humor.
Website: DataRevelations.com
Jeffrey A. Shaffer is Vice President of Information Technology and Analytics at Recovery Decision Science and Unifund. He is also Adjunct Professor at the University of Cincinnati, where he teaches Data Visualization and was named the 2016 Outstanding Adjunct Professor of the Year.
He is a regular speaker on the topic of data visualization, data mining, and Tableau training at conferences, symposiums, workshops, universities, and corporate training programs. He is a Tableau Zen Master, and was the winner of the 2014 Tableau Quantified Self Visualization Contest, which led him to compete in the 2014 Tableau Iron Viz Contest. His data visualization blog was on the shortlist for the 2016 Kantar Information is Beautiful Awards for Data Visualization Websites.
Website: DataPlusScience.com
Andy Cotgreave is Technical Evangelist at Tableau Software. He has over 10 years' experience in data visualization and business intelligence, first honing his skills as an analyst at the University of Oxford. Since joining Tableau in 2011, he has helped and inspired thousands of people with technical advice and ideas on how to build a data-driven culture in a business.
In 2016 he ran the MakeoverMonday (http://www.makeovermonday.co.uk/) project with Andy Kriebel, a social data project which saw over 500 people make 3,000 visualizations in one year. The project received an honourable mention in the Dataviz Project category of the 2016 Kantar Information is Beautiful Awards.
Andy has spoken at conferences around the world, including SXSW, Visualized, and Tableau's customer conferences. He writes a column for Computerworld, Living with Data (http://www.computerworld.com/blog/living-data/), as well as maintaining his own blog, GravyAnecdote.com.
Website: GravyAnecdote.com
Introduction
We wrote The Big Book of Dashboards for anyone tasked with building or overseeing the development of business dashboards. Over the past decade, countless people have approached us after training sessions, seminars, or consultations, shown us their data, and asked: “What would be a really good way to show this?”
These people faced a specific business predicament (what we call a “scenario”) and wanted guidance on how to best address it with a dashboard. In reviewing dozens of books about data visualization, we were surprised that, while they contained wonderful examples showing why a line chart often works best for time-series data and why a bar chart is almost always better than a pie chart, none of them matched great dashboards with real-world business cases. After pooling our experience and enormous collection of dashboards, we decided to write our own book.
How This Book Is Different
This book is not about the fundamentals of data visualization. That has been done in depth by many amazing authors. We want to focus on proven, real-world examples and why they succeed.
However, if this is your first book about the topic of data visualization, we do provide a primer in Part I with everything you need to know to understand how the charts in the scenarios work. We also dearly hope it whets your appetite for more, which is why this section finishes with our recommended further reading.
How This Book Is Organized
The book is organized into three parts.
Part I: A Strong Foundation. This part covers the fundamentals of data visualization and provides our crash course on the foundational elements that give you the vocabulary you need to explore and understand the scenarios.
Part II: The Scenarios. This is the heart of the book, where we describe dozens of different business scenarios and then present a dashboard that “solves” the challenges presented in those scenarios.
Part III: Succeeding in the Real World. The chapters in this part address problems we've encountered and anticipate you may encounter as well. With these chapters – distilled from decades of real-world experience – we hope to make your journey quite a bit easier and a lot more enjoyable.
How to Use This Book
We encourage you to look through the book to find a scenario that most closely matches what you are tasked with visualizing. Although there might not be an exact match, our goal is to present enough scenarios that you can find something that will address your needs. The internal conversation in your head might go like this:
“Although my data isn't exactly the same as what's in this scenario, it's close enough, and this dashboard really does a great job of helping me and others see and understand that data. I think we should use this approach for our project as well.”
For each scenario we present the entire dashboard at the beginning of the chapter, then explore how individual components work and contribute to the whole.
By organizing the book based on these scenarios and offering practical and effective visualization examples, we hope to make The Big Book of Dashboards a trusted resource that you open when you need to build an effective business dashboard. To ensure you get the most out of these examples, we have included a visual glossary at the back of this book. If you come across an unfamiliar term, such as “sparkline,” you can look it up and see an illustration.
We also encourage you to spend time with all the scenarios and the proposed solutions as there may be some elements of a seemingly irrelevant scenario that may apply to your own needs.
For example, Chapter 11 shows a dashboard used by a team in the English Premier League to help players understand their performance. Your data might have nothing to do with sports, but the dashboard is a great example of showing current and historical performance. (See Figure I.1.) That might be something you have to do with your data. Plus, if you skip one scenario, you might miss a great example of the exact chart you need for your own solution.
Figure I.1 A player summary from an English Premier League Club
(Note: Fake data is used.)
We also encourage you to browse the book for motivation. Although a scenario may not be a perfect match, the thought process and chart choices may inspire you.
Succeeding in the Real World
In addition to the scenarios, an entire section of the book is devoted to addressing many practical and psychological factors you will encounter in your work. It's great to have theory- and evidenced-based research at your disposal, but what will you do when somebody asks you to make your dashboard “cooler” by adding packed bubbles and donut charts?
The three of us have a combined 30-plus years of hands-on experience helping people in hundreds of organizations build effective visualizations. We have fought (and sometimes lost) many “best practices” battles. But by having endured these struggles, we bring an uncommon empathy to the readers
