Now You See It: Simple Visualization Techniques for Quantitative Analysis |  | Author: Stephen Few
Publisher: Analytics Press
Category: Book
List Price: $45.00
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Rating:  16 reviews
Sales Rank: 5,232
Media: Hardcover
Edition: 1st
Pages: 329
Number Of Items: 1
Shipping Weight (lbs): 3.5
Dimensions (in): 11.2 x 8.7 x 1.3
ISBN: 0970601980
Dewey Decimal Number: 650
EAN: 9780970601988
ASIN: 0970601980
Publication Date: April 1, 2009
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Product Description
Now You See It: Simple Visualization Techniques for Quantitative Analysis teaches simple, practical means to explore and analyze quantitative data--techniques that rely primarily on using your eyes. This book features graphical techniques that can be applied to a broad range of software tools, including Microsoft Excel, because so many people have nothing else, but also more powerful visual analysis tools that can dramatically extend your analytical reach. You'll learn to make sense of quantitative data by discerning the meaningful patterns, trends, relationships, and exceptions that measure your organization's performance, identify potential problems and opportunities, and reveal what will likely happen in the future. Now You See It is not just for those with "analyst" in their titles, but for everyone who's interested in discovering the stories in their data that reveal their organization's performance and how it can be improved.
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Showing reviews 1-5 of 16
 Visualization Tools For Business Analytics June 20, 2009
Rich Johnson (Bay Area, CA)
55 out of 59 found this review helpful
"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.
Recommendation
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.
Great introduction to Visual Analysis July 15, 2009
Jock D Mackinlay
14 out of 17 found this review helpful
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.
Clear and calm guide to info visualization June 23, 2009
Ben Shneiderman (College Park, MD USA)
10 out of 13 found this review helpful
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.
the gospel of visual analysis March 18, 2010
Jerome Cukier (Paris, France)
1 out of 1 found this review helpful
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.
Stephen Few Continues to Enlighten! June 8, 2009
Anthony J. Rose (Columbia, MD United States)
9 out of 13 found this review helpful
Stephen continues to enlighten his readers by sharing essential theories of data visualization using brilliant examples from different software like: Excel, Spotfire and Tableau. I would almost consider this book a prequel to his other books - Show Me the Numbers: Designing Tables and Graphs to Enlighten and Information Dashboard Design: The Effective Visual Communication of Data because it discusses many ideas about why visualizations should be created a certain way for them to be optimal.
The book doesn't waste any time with dragging out the history of data visualization and jumps right into his ideas and theories. Few also designs this book so that it can be used by people is many different sectors as well as software developers. By using separate text boxes, Few has provided requirements for anyone interested in designing software or programs to visualize data.
The sequence of the book was nicely done by putting the core concepts and principals first and building upon them by looking at specific skills, patterns and techniques. The book finishes with some thoughts about the future of data visualization and keeps you wanting more. Stephen has a gift for writing about data visualization in a way that is straight-forward, simple and yet very informative no matter what your background is or field you study or work in.
I highly recommend this book to anyone who is either involved with data or designing software for data analysis or visualization. I can easily see this text being recommended reading in courses and a staple in the library of anyone who works with data.
Showing reviews 1-5 of 16
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