Technological advances, datasets becoming larger, more people having access to data, and public and policy makers asking for more information from the agencies that collect data. These are just a few of the reasons why the field of data visualization is becoming increasingly important.
In other words, data visualization is more than just graphs, it is a way of accurately and effectively communicating the data and the story it tells to your stakeholders .
You may also want to entertain your audience using various design principles, but doing this can actually distort the data or the message and more importantly the decisions based on the display. Therefore, data visualization should be used only as a tool which would hold data integrity as primary and supplement it with high quality design principles that add value to the data users.
I wanted to share some books that I've personally found useful in this area. I especially like them because they show examples of what to do and what not to do. A word of warning however: once you learn what bad elements of data visualization are, you tend to see them everywhere. If you see them in your own work, eliminate them. If you see them in the work of others, very kindly let them know.
- Envisioning Information, Tufte, 1990
- How to Lie With Statistics, Huff, 1993 (reprint from 1954)
- Visualizing Data, Cleveland, 1993
- Visual Explanations: Images and Quantities, Evidence and Narrative, Tufte, 1997
- The Visual Display of Quantitative Information, Tufte, 2001
- Show Me the Numbers: Designing Tables and Graphs to Enlighten, Few, 2004
- Beautiful Evidence, Tufte, 2006
- Visualize This: The FlowingData Guide to Design, Visualization, and Statistics, Yau, 2011
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