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Data Insights

Book Description

Data Insights offers multi-disciplinary perspectives and useful information about how visualizations can open your eyes to data. This thought-provoking book takes a conversational approach to presenting an overview of the subject, while also focusing on key details. It highlights the ideas and work of a variety of people who are actively contributing to this still emerging field. Case studies from business analytics, healthcare, games, security, and network monitoring, among others, portray what is going on in data visualization today. A diverse blend of original illustrations and real-world examples, both classical and cutting-edge, help fill in the picture.

This book provides an approachable overview of important aspects of data visualization, and…

  • Demonstrates, with a variety of case studies, how visualizations can foster a clearer and more comprehensive understanding of data
  • Answers the question, "How can data visualization help me?" with discussions of how it fits into a wide array of purposes and situations
  • Makes the case that data visualization is not just about technology; it also involves a deeply human process


  • Demonstrates, with a variety of case studies, how visualizations can foster a clearer and more comprehensive understanding of data
  • Answers the question, "How can data visualization help me?" with discussions of how it fits into a wide array of purposes and situations
  • Makes the case that data visualization is not just about technology; it also involves a deeply human process

Table of Contents

  1. Cover image
  2. Title page
  3. Table of Contents
  4. Copyright
  5. Dedication
  6. Preface
    1. Sandboxes and Museum Cases
  7. Acknowledgments
  8. About the Author
  9. Chapter 1. From Terabytes to Insights
    1. Introduction: A Grander View
    2. Things That Make Us Smarter: How Thoughtful Visualizations can make our Lives Better
    3. Don’t Be Afraid of the Chart
    4. PEER AT the World of Data
    5. From Data to Wisdom
    6. A Day with Data
    7. The Torrents and Trickles of Data: Observations from Statistician John Bosley
    8. Cascades of Confusion
    9. The Data Lifecycle
    10. “Just the Facts”: What are Data and Metadata?
    11. What to Leave in and What to Leave Out: A Conversation with Journalism Professor and Tech Entrepreneur, Len Sellers
    12. What Counts?
    13. The Ripple Effect
    14. Attributes of Data Visualization
    15. Diving into the Well of Machine Data with Splunk Cio Doug Harr
    16. Deep Simplicity (Complex Data in Simple Forms)
    17. What’s New?!
  10. Chapter 2. A More Beautiful Question
    1. The Art of Inquiry
    2. Good Question
    3. Washington, D.C.’s 1100 Points of Light
    4. Twenty Questions
    5. Patterns, Contexts, and Questions
    6. Designing Software for When You Don’t Know What You Don’t Know
    7. The Questions within a Question
    8. Knowing What You’ve Got
    9. Questions and Metadata
    10. Quick Questions
    11. Finding “Personal Bests” (Based on Work by Information Scientist, Dan Gillman)
    12. Lowering the “Curiosity Tax” for Businesses
    13. Asking Good Questions
    14. Approaching Data with a Beginner’s Mind
    15. TMD (Too Much Data)?
    16. A More Beautiful Question
  11. Chapter 3. Winning Combinations: Working with the Ingredients of Data Visualization
    1. Just the Right Mix
    2. Counter intelligence: Figuring Out what to do with Many Ingredients
    3. Setting the Table
    4. Part One: Selecting, Storing, and Combining the Ingredients of Data
    5. Part Two: Fitting Data Types with Visual Forms
    6. Color!
    7. Part Three: Putting Together Different Kinds of Visualizations
    8. A Winning Collaboration on a Small Scale
    9. Conclusion
  12. Chapter 4. Pathways, Purposes, and Points of View
    1. Along These Lines…
    2. Following Strands of Data
    3. On the Road Again
    4. Tangible and Intangible Pathways
    5. Pathway and Process
    6. Finding Rare Birds in Dense Jungles: A Packing List
    7. Time Travel, Tracks, and Wakes: Visualizing Flux and Data
    8. Data and the Narrative Path
    9. Crossing Points and Graph Visualizations
    10. Bridges, Networks, and Roles
    11. Dots with Advanced Degrees
    12. More than Dots on a Map (Perspectives from Ushahidi’s Patrick Meier)
    13. More than Just Data Points
    14. Points to Remember
  13. Chapter 5. Views You Can Use
    1. Getting Through
    2. Perceiving the Gray Areas
    3. It All Depends on Your Perspective
    4. Data Models versus User Models
    5. Enabling versus Imposing Mental Models
    6. User Experience Design and Making Sense of Data
    7. Can you spare some change?
    8. Learned Interfaces versus Intuitive Interfaces
    9. T2—Technology × Training
    10. Left to Your Own Devices
    11. Baseballs, Bassoons, and Virtuosity
    12. Sound Advice from HCI and Shneiderman’s “Golden Rules”
    13. Usability and Data Visualization
    14. Looking at User-Driven Design With Tom Sawyer Software Ceo Brendan Madden
    15. A Look at the Landscape: Color and Composition With Artist Walt Bartman
    16. In Review...
  14. Chapter 6. Thinking … Machines
    1. The Yin-Yang of Data Analysis
    2. Scaling-Up Analysis: Knowledge, Data Mining, Machine Learning
    3. Entering the Mine
    4. Manual and Automatic
    5. Automated Observations and Human Hypotheses
    6. Black Boxes, Toy Boxes, and Out of the Box
    7. Gut-Checks and Algorithms
    8. Consternation About Correlation and Causation
    9. The Shape of Things to Come?
    10. Knowing How to Fold ’Em
    11. Multiple Intelligences and Data Visualization
    12. Questions, Ideas, Insights
    13. Humans, Computers, and Collaborations
    14. The Sum of the Parts
  15. Chapter 7. Hindsight, Foresight, and Insight
    1. Part 1—Adapting to Data
    2. Keeping Pace
    3. Part 2—New Dimensions in Data Visualization
    4. Part 3—Real Time
    5. The Elephant in the Room
    6. Border Crossings...
  16. Resources
  17. References
  18. Index