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Index
Cover
Title page
Table of Contents
Copyright
Dedication
Foreword
Introduction
About the Author
Acknowledgments
Part I: How Data is Driving Business Disruption, Transformation, and Reinvention
Introduction
Chapter 1: Separating leaders from laggards
Abstract
1.1. An era of disruption, transformation, and reinvention
1.2. Characteristics of data-centric companies
1.3. Examples of data-driven companies
1.4. From the data to the dashboard
1.5. Navigating this book
Chapter 2: Improved agility and insights through (visual) discovery
Abstract
2.1. The discovery imperative
2.2. Business intelligence versus data discovery
2.3. The business impact of the discovery culture
2.4. The role of friction in discovery
2.5. The four forms of discovery
2.6. SQL: The language of discovery
2.7. Discovery in the days to come
Chapter 3: From self-service to self-sufficiency
Abstract
3.1. From self-service to self-sufficiency
3.2. Discovery capabilities for self-sufficiency
3.3. (Information) enablement technology
3.4. The data scientist: the sexiest of them all
3.5. Moving forward
Chapter 4: Navigating ethics in the big data democracy
Abstract
4.1. Introduction
4.2. Aftershocks of the big data revolution
4.3. Big data’s personal impact
4.4. Exercise: ethical data scenarios
4.5. Data ethics in the news
4.6. The data visualization hippocratic oath
4.7. Ethics requires leadership
4.8. Closing thoughts
Chapter 5: The data science education and leadership landscape
Abstract
5.1. Introduction
5.2. The new data science student
5.3. The new digital native
5.4. Addressing the gender gap—women in IT
5.5. New roles for new leaders
5.6. The steps beyond
Part II: Communicating Data Visually
Introduction
Chapter 6: Visual communication and literacy
Abstract
6.1. The history of visual communication
6.2. Visual memorability and retention
6.3. Extending visual literacy to visual data literacy
6.4. From communication to conversation
Chapter 7: Visual storytelling with data
Abstract
7.1. The storytelling paradigm: defining the data story
7.2. A brief bit of story psychology
7.3. The data narrative framework
7.4. Five steps to data storytelling with visualization
7.5. Storytelling reconsidered, the probability problem
7.6. Storytelling’s secret ingredient: the audience
Chapter 8: The importance of visual design
Abstract
8.1. Data visualization is a beautiful science
8.2. Key cognitive elements in visualization
8.3. Color 101
8.4. Visual design building blocks
8.5. Visualization constraints
Chapter 9: The data visualization continuum
Abstract
9.1. Data visualization definition
9.2. The power of viz
9.3. To explain or explore—or both?
9.4. The rise of the infographic
9.5. Choosing the chart: a quick diagnostic
9.6. Data visualization golden rules
9.7. Conclusions
Part III: Building the Foundation for Data Visualization
Introduction
Chapter 10: Architecting for discovery
Abstract
10.1. Key information challenges for data discovery
10.2. Tackling today’s information challenges
10.3. Designing for frictionless
10.4. Enabling governed data discovery
10.5. Conclusions
10.6. Anatomy of a visual discovery application
10.7. The convergence of visual analytics and visual discovery
Chapter 11: Data visualization as a core competency
Abstract
11.1. Data visualization business benefits and risks
11.2. Introducing the data visualization competency center
11.3. Tools for the DVCC
11.4. Socializing the DVCC
11.5. The implementation roadmap
11.6. Four tips to DVCC success
Chapter 12: Visual discovery by design
Abstract
12.1. Data discovery by design
12.2. Leveraging visualization for assessable, meaningful, actionable
12.3. Three key points to a useful data visualization
Chapter 13: The need for visualization in the Internet of Things
Abstract
13.1. Understanding “data in motion”
13.2. The internet of things primer
13.3. The art of animation
13.4. Human centered design in mobile(first) strategies
13.5. Interaction for playful data visualization
Appendix
Subject Index
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