Customer Reviews: Now You See It: Simple Visualization Techniques for Quantitative Analysis
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on June 20, 2009
"Now You See It" is the latest book by author Stephen Few. The description says this book is a companion to "Show Me The Numbers," which is a favorite book of mine. "Show Me The Numbers" is about building charts and tables that will help you show others what you see in your data. "Now You See It" is about helping you to find new ways to display your data for your own analysis. Before you can show others your data you need to understand it yourself, and that's where this book fits in.

Creating charts is front and center as the focus of this book. "Show Me The Numbers" focused on charts and tables that could be built with simple tools such as Excel. Now You See It shows you the types of analysis you can do when you employee more advanced software such as Tableau and R. Some of the illustrations are really cool to look at and inspirational, even if I will never have the tools or time to prepare my own version of them.

"Now You See It" is broken up into 3 sections:

In Part 1 - Building Core Skills for Visual Analysis. Stephen Few covers the history of information visualization, the basics of analysis, and how we perceive data. There is some overlap with "Show Me The Numbers," but it's only one chapter, and not a deal breaker for me. I found the history of information visualization chapter interesting, and I imagine that in 50-100 years there are going to be new kinds of visualization methods available that we haven't even thought of yet.

In chapter 4, Analytical Interaction and Navigation, the author covers the role of good software in the data analysis process. He lists a few requirements that good software should have, and in many cases popular software such as Excel fall short. This is when you realize that learning another program like R could be useful. I almost feel like this chapter was written for software developers who are trying to create their own data analysis software, so if you're in that camp this is your book.

Part 2 - Honing Skills for Diverse Types of Visual Analysis, goes in depth with various types of charts that you can use to analyze your data. There is a chapter for each of the major types of visual analysis: Time Series, Ranking and Part-to-Whole, Deviation, Distribution, Correlation, and Multivariate.

Within each chapter Stephen Few shows you which types of patterns you should look for in your data and shows you what those patterns mean. He then shows you different ways of displaying the data, which can range from simple Excel charts to complex visualizations which could belong in a magazine. Finally he finishes each chapter with a list of best practices for analyzing the data, such as scaling chart intervals properly or using logarithmic scales to compare the percent change of data with different starting points (look at almost any stock market graph to see a logarithmic chart in action).

These chapters form nearly 50% of the book, and could be very useful reading to a student getting started with statistics, or anyone else who is not completely comfortable with numbers.

Part 3 - Further Thoughts and Hopes. The first chapter of the book opens with the history of information visualization, and the final chapters conclude with the author's thoughts on the future. As computing power gets stronger and the internet becomes more ubiquitous new innovations are in the works, and some of them are covered here.


I finished reading this book about a week ago, and at first I didn't think much of it. I already have a strong analytical background and didn't feel like I got much out of this book in terms of learning anything new. But after a few days I noticed that I starting thinking about problems differently - I started thinking about how I could present them in a visual manner, and I started sharing my simple charts with others.

I am finding that being able to throw together a chart quickly and effectively is extremely helpful for me and a great way to share results with coworkers. Despite having seen almost everything in this book before, reading it has got me thinking about using charts more to analyze data. It is also the kick I needed to start learning to do charts in SAS so I can expand my visualizations beyond what Excel can do.

The benefits of this book may not be immediately apparent like "Show Me The Numbers,", but if you give it some time to sink in I think you will start thinking of new ways to visualize your data. The charts shown by Few in this book are, for the most part, accessible to those of us in business, versus Edward Tufte who emphasizes charts created with design tools such as Adobe Illustrator. There are some examples shown in Tableau and Spotfire, which are both quite expensive. But there are also illustrations created in R, which is free. Of course if you are going to use those programs you have to learn to use them, but that will only increase your job appeal that much more.

If you work as a business analyst and are looking for practical ways to expand your knowledge and abilities, I highly recommend this book.
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on November 13, 2009
Stephen Few has put together a book that is useful as a reference but readable as well. I heard him speak at a conference and really think he has hit the mark. The book is accessible without being shallow. He gives worthwhile examples of how to combine the features of the software with good graphing techniques. As someone who has worked with many of the techniques, he provides a reason for what I did intuitively. This is invaluable for both displaying findings and training subject experts to analyze their data.
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on July 15, 2009
As someone who's done over two decades of research and development on visualization technology, I highly recommend "Now You See It" for everybody - novice to expert. Stephen Few explains visual analysis clearly and conversationally. His examples are accessible, appropriate, and beautiful.

The book is well-structured. Part I focuses on core concepts, principles, and practices. It prepares the general reader for Part II, which focuses on more technical material involving specific types of analysis (time-series, deviation, correlation, etc). Part II contains practical advice that will help everyone become better at visual analysis.

I particularly like the recommendations Stephen Few has included for visual analysis techniques that should be supported by commercial systems that are helping us work with data. After all, computers are now automatically collecting data. This book teaches us how to use this data to inform our individual work and to enhance our communication with each other. I believe these are key skills that will help us improve our modern, complex world.
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on June 23, 2009
Clarity and calm are great virtues in making difficult problems seem easy. Stephen Few offers an abundance of these virtues in his book, Now You See It: Simple Visualization Techniques for Quantitative Analysis. He methodically guides readers from example to example in an orderly journey made even more tranquil by his gentle personal style of writing. The "I", "you", and "we" phrasing make for easy reading, even as the information visualization concepts get progressively more complex and potent.

The example data sets are easy to understand and the lessons of good design seem to pop up from the surface of the pages. Color is used cautiously and appropriately, with no wasteful distractions. The clean designs show respect for Tufte's data-to-ink ratio.

As early as 1965, statistician John Tukey recognized that one of the great payoffs of interactive computing was the potential for exploratory data analysis. Stephen Few reiterates Tukey's vision and then fulfills it by showing that good graphical representations "pave the way to analytical insight." Few has a potent advantage in that modern software tools enable him to show off the good and bad approaches for each concept. Successful commercial tools like Spotfire and Tableau are put to work repeatedly, while university research projects show up where appropriate. Over all, Few lays out the territory and gives us a grand tour.

Few closes with this declaration: "I love information, in part for the understanding that it offers...Mostly, though, I love it for what I can do with it to leave the world a little better off than I found it." Few proudly presents this noble aspiration to his readers in a compelling way; now it's up to us to realize this goal through the emerging discipline of information visualization.
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on May 7, 2014
I'm only on page 53, starting chapter 4, but Stephen broke it down line by line. Literally! I am a Senior in college and I figured out why I struggle in college. It's not that I am stupid. The authors who write books write them with YEARS of experience (15, 20, 25, etc) under their belt. I guess they forgot the simple stuff. They never did teach ANYTHING about ways to improve our memory to aid in data analysis. Basically, here's some charts, study them, understand the material, and if you don't understand it, "you need to study harder". The teacher only says that because he/she doesn't know the correct answer. Anyway, thanks for the excellent book. It really is a great deal. It's hard cover (although made of a flimsy cardboard) and protects the pages. The paper is great quality and includes some colored graphics. Colleges should consider this book for their programs. It's that valuable. I'm Gen Y and I learn different than my predecessors. All I need is a basic understanding of material and I've got it. This book CERTAINLY does that. It provides the history, mental cognition tools, ways to improve memory, errors in graphing, etc. I am only on page 53 and I've learned that much. MORE than my University has taught me. We need more books like this. Thank you! I forgot to add, this book is well written. And below market price. It's a wealth of information.
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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 February 15, 2012
"Now You See It" is like a modern version of Edward Tufte's books because it focuses on interactive visualization rather than on creating static charts. It looks like a textbook but reads like a novel. I actually look forward to taking a lunch break and reading it. It presents the key principles of data visualization with easy-to-understand examples and great visuals. I have a number of years of experience in biomedical research and am currently doing data analysis on the administrative side of academia. But I have little formal training in stats. I mainly purchased the book to help with selecting and learning how to use one of the many data visualization tools on the market. "Now You See It" helped me understand both what features are important in selecting a tool, and how I should use it once we purchase one. I feel I have a much better understanding of how to make good visualizations after reading this book, and am really excited about the possibilities.
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on March 18, 2010
I've read Stephen's book about 6 months ago, and found it then very interesting. But I am only starting to appreciate its true greatness.
What must first be said about Stephen's writing is that he's first and foremost a teacher. As such, he is very good at explaining a subject in a way that the reader understands it with minimum effort, and with no pre-requisite knowledge. His writings are very accessible, but are also well-constructed: he doesn't just handle his point of view, but justifies his recommendations in a way that makes perfect sense. And he manages to do so without being dogmatic. On top of that, I really appreciate the quality of his language, which is simple enough for folks like me (English is not my 1st language) yet subtle enough to convey the finesse of his arguments.

Anyway. The above can be said of all 3 books of Stephen Few. So what makes Now you see it so great?
people who've worked in the field of visual analysis for some time are well aware of what vendors can do for them and tend to focus on the capabilities of a specific solution, rather than on the business needs of their organisations. Such practitioners may not feel that they are learning much from reading the book.
on the other end of the spectrum, decision makers in the broad sense have typically no idea of how visual analysis can make their life easier. And they could be awed by a novel tool, which may not be appropriate for their needs - but how could they know?

this book, which does a superb job of explaining the hows and whys of visual analysis, can really enlighten managers and present them with a world of possibilities they didn't suspect exist. but it can (should) also be used by data visualization experts to explain the interest of their discipline to their colleagues in terms they can understand, to empower them with enough knowledge to take the right decisions. This book with its clear logic and examples is a great tool of evangelization.
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on May 23, 2010
Like Tufte, Few is a well-known evangelist for clear data visualizations that yield actionable insights. Unlike Tufte, Few is more of a craftsman and less of an artist: his style is less elegant than Tufte's, but for that reason I actually find his advice has greater practical value. Tufte's graphics inspire and awe me in the same way that a Bach fugue does, but I can scarcely imagine creating anything so elegant myself. Few gives examples that I can actually emulate in my work.

PS: I have met Tufte in person, but have never met Few though I'd like to!
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on January 6, 2013
This is the first book purchased for use in my PhD program, and at work, that I have felt others should read. I mention my current academic undertaking only because the academic world suffers as badly as the business world when it comes to actually communicating quantitative information. The author starts by stating that we have an information problem; that we have too much to digest effectively without changing our methods. I disagree. What we have is mounds and mounds of unorganized data that too few people have taken the effort to turn into useful information.

The author's (achieved) goal was to provide a number of methods by which that data can be used more effectively. But he does more than provide a catalog of methods. He shows how some of them are better in one situation, and that other methods are better in other situations or when the presenter's goals are different. By doing so, he has also given us a very nice set of tools for determining if the next graph or chart is failing to provide all it can or if the presenter is misleading his audience. Mr. Few provides figures on nearly every page of the book and does an outstanding job of explaining them.

This book will be referred to often in my career.
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