Data visualization is about presenting data in a way to help humans interpret, analyze, learn from it, and most important in a business context, take action on it. More than just objectively showing a result of data discovery or analysis, visualization can point a user in one direction or another based on the data chosen, the techniques used, and the creator’s focus. This book focuses on the narrative part of data visualization. It’s an excellent addition to this series, which has mostly focused on the infrastructure and algorithms of data and analytics. Visual representation is the end result of all that work on the back end, which means this book closes the loop on the overall analytics story. Despite its focus on Tableau as a tool, the concepts and methods discussed throughout are applicable to any data tool, be it Excel, custom visualizations, or other products that give analysts and data scientists the ability to tell a story through data.
Lindy has deep experience in analytics, communication, and data visualization. She led research in visual analytics, among other things, at Radiant Advisors before moving into academia where she now teaches on data analysis, communication, and visualization at both Rutgers University and Montclair State University, as well as actively researches in the field at Rutgers Discovery Informatics Institute. She brings her depth of experience to this book with explorations and analysis of some famous and well-known data visualizations in addition to lessons on choosing different visuals, color palettes, data preparation, charts, and more.
Two of the three primary takeaways from this book are broadly applicable to any developer, business analyst, executive, journalist, or student regardless of which tool they use. Specifically, the first takeaway focuses on giving the reader the knowledge to evaluate visualizations for their effectiveness and determine how best to tell a story with their data. The second focuses on how to present this data and focus on the audience for maximal impact. Finally, the third takeaway of the book is to use Tableau as a tool to produce compelling visualizations from diverse data sources and types. This book is a great addition to the series for any reader wanting to learn how to create the most impactful stories possible around their data, and to apply hands-on skill learning with today’s best data visualization tools.
—Paul Dix, Series Editor, Addison-Wesley Data & Analytics Series