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on 24 January 2015
I had moderate expectations buying this book and unfortunately it has been a disappointment. The book is too basic, the examples are simplistic. For most of the book, the author is trying to define what functionality the perfect visualization software should have. I was hoping for more examples of customized solutions I cannot find in the menu of a typical visualization software package. This book might be helpful to a beginner as it is simple and well organized. I cannot recommend it to anyone who has worked as an analyst, though. I personally find Gene Zelazny's book much more helpful.
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on 14 August 2009
This is another practical, clear book from Stephen Few, along the lines of his Dashboards book, but weightier.

Contains numerous examples using modern software such as Tableau and Spotfire, but also tips on beating Excel into submission.

The focus of this book is displays for analysis and understanding, rather than for presentation or monitoring (dashboards). The book therefore covers some displays (such as parallel coordinate plots) that only really work when used dynamically, rather than being static slides or paper printouts.

Sidebars throughout the book give succinct requirements that good information visualisation software should support, such as "provide a means to easily filter all tightly-coupled tables and graphs together by a single action".

Much of the material I have seen before, but this is still a useful collection of 'good practice' for common display types such as line graphs and dot plots, and a good source book for less-well known types of graph.
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Stephen Few introduces the visual analysis of data. He shows readers how to discover patterns in large data sets through clever arrangement, highlighting and filtering of data points. I encountered the book as the text in a four-week online class on visual data analysis. But it also works well as a standalone introduction to this area.

The first half of the book has a different focus than I expected. Few suggests that "...we've largely ignored the primary tool that makes information meaningful and useful: the human brain. While concentrating on the technologies, we've forgotten the human skills that are required to make sense of the data." He describes the human visual system, how it processes information, and the errors in perception it sometimes makes. His emphasis, however, is on the strengths of visual perception which he links to best practices in data analysis. One of the most useful parts of this section is in Chapter 2, where he lists and describes the "aptitudes and attitudes of effective analysts."

The book's second half describes and illustrates specific visual analysis techniques. It is rich with visual examples, comparisons of effective and ineffective displays, and series of related visualizations which show incremental steps of data transformation and analysis. Chapters are organized by specific data patterns and analytical techniques, describing how to look for the following six kinds of patterns:

- Time-series
- Ranking and part-to-whole relationships
- Deviations
- Distributions
- Correlations
- Patterns in multivariate data

Two final chapters present recommendations for developers of data analysis software and make predictions about future trends in visual data analysis.

The book is recommended for any researcher who works with large data sets. It is well-written, contains clear examples, and references recent research and the latest tools available for data analysis. Readers may also be interested in Few's Show Me the Numbers: Designing Tables and Graphs to Enlighten which discusses how to best describe patterns in data to nonresearchers.
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on 18 August 2009
This book has great insights on how to design user efficient graphs. Most of the examples are nicely and brightly illustrated.

I haven't read everything yet but so far, so good.

I also recommend reading the excellent "Information Dashboard Design" from the same author (the reason I bought this book).
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on 15 March 2011
A pretty boring read if you go at it cover to cover, which was the way I started.
As a reference book, however, it is excellent, and highly recommended.
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on 31 August 2014
Excellent book to learn quantitative data analysis
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