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Product Description
This companion to Show Me the Numbers teaches the fundamental principles and practices of quantitative data analysis. Employing a methodology that is primarily learning by example and “thinking with our eyes,” this manual features graphs and practical analytical techniques that can be applied to a broad range of data analysis tools—including the most commonly used Microsoft Excel. This approach is particularly valuable to those who need to make sense of quantitative business data by discerning meaningful patterns, trends, relationships, and exceptions that reveal business performance, potential problems and opportunities, and hints about the future. It provides practical skills that are useful to managers at all levels and to those interested in keeping a keen eye on their business.
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Most Helpful Customer Reviews
14 of 15 people found the following review helpful
Format:Hardcover|Amazon 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.
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.
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.
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.
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.
5 of 9 people found the following review helpful
Format:Hardcover
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).
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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