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Now You See It Hardcover – 30 Apr 2009

4.0 out of 5 stars 6 customer reviews

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Product details

  • Hardcover: 329 pages
  • Publisher: Analytics Press (30 April 2009)
  • Language: English
  • ISBN-10: 0970601980
  • ISBN-13: 978-0970601988
  • Product Dimensions: 21.6 x 3.3 x 27.9 cm
  • Average Customer Review: 4.0 out of 5 stars  See all reviews (6 customer reviews)
  • Amazon Bestsellers Rank: 138,235 in Books (See Top 100 in Books)

Product Description

About the Author

Stephen Few is the author of "Information Dashboard Design: The Effective Visual" "Communication of Data," " Show Me the Numbers: Designing Tables" "and Graphs to Enlighten," and the monthly "Visual Business Intelligence" newsletter. He has worked for more than 25 years as an information technology innovator, teacher, and consultant. As the principal of the consultancy Perceptual Edge, he focuses on practical uses of data visualization to explore, analyze, and present quantitative business information. He lives in Berkeley, California.


Customer Reviews

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Top Customer Reviews

Format: Hardcover Verified Purchase
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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Format: Hardcover Verified Purchase
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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Format: Hardcover
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.
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