In case if some publisher wants to publish a book about Data Visualization based on this blog, I can write it with the following Name, Summary, Content and Outline:

Name of the Book: Visible Data


Book Summary.

This book about processes, methods and tools for Data Visualization. It explains how to make your Data Visible, how to Discover, Analyze, Pivot, Explore, Drilldown, Visualize and Interact with your data and how to make it actionable…

Outline of the Book.

 1. Introduction into Data Visualization and Visible Data.

Outline: Data, Story and Eye Candy, Data Visualization, Visible Data, Discovery of To-Do and Action List.

2.   History of Data Visualization

Outline: Homma(candlestick), Playfair (line, pie, bar), Nightangale (radar), Minard (maps), Chartology.

3. Data Visualization as the path to Visible and Actionable Data

Outline: Prototypes, Life Cycle, Data Store, Engine and Flow, Operations with Visible Data, Client and Server Software.

4. Data Views and Visibility of Data.

Outline: Types and Choices of Charts (30+), and their Dimensionality (from 0 to 7); KPIs, Dashboards and Scorecards.

5. Backend Data processes.

Outline: Data Collection, Extraction, Transformation, Load, Cloud, Cubes, Columnar Databases, Big Data.

6. Visible Data Operations.

Outline: Data Exploration, Filters and Sorting, DrillDown, Visual Analytics, Trends, Outliers, Clusters and other Data Patterns

7. Location Intelligence.

Outline: GeoGoding, Filled Maps, Maps and Charts

8. Time and Series Intelligence.

Outline: Well Ordered Datasets, Time Series, Trends, Timelines, Correlation, Regression, Extrapolation and Forecasting.

9. Sources of Visible Data and unintrusive Data Access.

Outline: Data Stores, SQL Views, Replication, Files, in-memory Data Engines, Reload, Refresh and Update of Visible Data.

10. User Management with Data Visualization Systems.

Outline: Security, Authentication, Licensing, User Groups, Privileges and Roles

11.  User Interfaces for Visible Data.

Outline: Fonts, Colors, Palettes, Borders, Backgrounds, Shapes, Labels, Tips, Comments, Sharing, Messaging.

12. Client Software for Data Visualization.

Outline: Desktop Viewers, Readers and Players, Web, AJAX, HTML5 and Mobile Zero-Footprint Clients.

13.  Server, SaaS and Cloud Software for Data Visualization.

Outline: Application, Web, Publishing and Management Servers/Services.

14. Customization of Data Visualization Applications.

Outline: API, Scripting, Embedding, Application Integration, Web Deployment.

  •  Appendix A. Samples of Visible Data: Incidents, Tasks, Actions, Audits, Alerts; Green House Gases, Energy and Utility Usage, Flights

  • Appendix B. Making Data Visible: Market, Vendors and Comparison of best Data Visualization tools.

  • Appendix C. More about Data Visualization: Public Data, Blogs, Websites, Demos and Tools related to Data Visualization.

  • Appendix D. Online Extension of the Book:


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