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Data Visualization: a successful design process, by Andy Kirk
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In Detail
Do you want to create more attractive charts? Or do you have huge data sets and need to unearth the key insights in a visual manner? Data visualization is the representation and presentation of data, using proven design techniques to bring alive the patterns, stories and key insights that are locked away.
"Data Visualization: a Successful Design Process" explores the unique fusion of art and science that is data visualization; a discipline for which instinct alone is insufficient for you to succeed in enabling audiences to discover key trends, insights and discoveries from your data. This book will equip you with the key techniques required to overcome contemporary data visualization challenges.
You’ll discover a proven design methodology that helps you develop invaluable knowledge and practical capabilities.
You’ll never again settle for a default Excel chart or resort to ‘fancy-looking’ graphs. You will be able to work from the starting point of acquiring, preparing and familiarizing with your data, right through to concept design. Choose your ‘killer’ visual representation to engage and inform your audience.
"Data Visualization: a Successful Design Process" will inspire you to relish any visualization project with greater confidence and bullish know-how; turning challenges into exciting design opportunities.
Approach
A comprehensive yet quick guide to the best approaches to designing data visualizations, with real examples and illustrative diagrams. Whatever the desired outcome ensure success by following this expert design process.
Who this book is for
This book is for anyone who has responsibility for, or is interested in trying to find innovative and effective ways to visually analyze and communicate data.There is no skill, no knowledge and no role-based pre-requisites or expectations of anyone reading this book.
- Sales Rank: #523184 in eBooks
- Published on: 2012-12-26
- Released on: 2012-12-26
- Format: Kindle eBook
About the Author
Andy Kirk
Andy Kirk is a freelance data visualization design consultant, training provider, and editor of the popular data visualization blog, visualisingdata.com.
After graduating from Lancaster University with a B.Sc. (Hons) degree in Operational Research, he spent over a decade at a number of the UK's largest organizations in a variety of business analysis and information management roles.
Late 2006 provided Andy with a career-changing "eureka" moment through the serendipitous discovery of data visualization and he has passionately pursued this subject ever since, completing an M.A. (with Distinction) at the University of Leeds along the way.
In February 2010, he launched visualisingdata.com with a mission to provide readers with inspiring insights into the contemporary techniques, resources, applications, and best practices around this increasingly popular field. His design consultancy work and training courses extend this ambition, helping organizations of all shapes, sizes, and industries to enhance the analysis and communication of their data to maximize impact.
This book aims to pass on some of the expertise Andy has built up over these years to provide readers with an informative and helpful guide to succeeding in the challenging but exciting world of data visualization design.
Most helpful customer reviews
11 of 11 people found the following review helpful.
disappointing and error-strewn
By Nick Cox
This to me is a very disappointing book, although if your tastes and
needs differ from mine you may like this book much more than I do.
First off, a fair test of a book on visualization is whether the
graphics look interesting or useful. Be warned that in this case the
printed book includes only muddy gray scale Figures, even though many
of the originals were in color; the text even refers to different
colors that you can supposedly see. It seems that you need the e-book.
I see no explanation of this limitation on the publisher's website. To
put the point as positively as possible, it seems that Packt are
mostly concerned with selling e-books. There is a partial apology for
the lack of color on the author's own website.
Be warned further that even when black-and-white reproductions make
sense the Figures are often hard to read, hard to understand, or both.
In many cases it is evident that you are expected to look at the
internet originals, which is not outrageous, but for others there is
no obvious source.
Second, and rather surprisingly, there is not that much on
visualization in any strict sense. The distinctive focus is largely on
the attitudes and habits you need to be like the author, a free-lance
designer developing substantial projects on commission. There is not
so much here for the student, scientist or employee with data and the
need to produce visualizations over the next few days.
The discussion makes many sensible points based on experience. An
enthusiastic, up-beat tone will appeal to many readers. But over many
long stretches the discussion reads more like a management or
self-help book with well-meaning but empty platitudes and labored
discussion of obvious points.
Throughout, the author writes in a very long-winded way. Often he
cannot put down a word without adding another that means almost the
same, as with "innovation and novelty", "developments and trends" and
many other examples. Oddly, the author on his website names Strunk and
White on style as a favorite, but it's years since I have read more
"needless words" that should have been omitted. Spelling, punctuation,
and word choice are frequently awry. If you are irritated by confusion
between "principal" and "principle" or "affect" and "effect", or by anything
else that would have infuriated your English teachers, then you are
likely to find this book painful to read. In total, there are
minor errors on virtually every page.
Third, this is not really a technical book, a problem if that is what you
seek. There is no code for any language or program, and no technical
guidance on (say) statistics. You are expected to get that from elsewhere,
which is fair enough, but beware that precise technical guidance is not
on offer beyond some elementary comments on different kinds of graphics.
But even on the technicalities it covers it is often inaccurate: the relations
between isarithmic, choropleth and topological (here a malapropism for
"topographical") maps are hopelessly confused. Minard's graphic on
Napoleon's retreat from Moscow is described as showing his advance,
which misses the main point by miles. (Thousands of miles?) More
importantly, the assertions that line charts and stacked area charts
are essentially for time series are neither correct nor helpful.
Fourth, the author's scholarship is that of the internet, not the library.
With a few bizarre exceptions books and papers are at best alluded to,
rather than precisely referenced. Although there are many useful-looking
URL references, you may feel short-changed by very scrappy literature
references if you are a student, scholar or scientist.
6 of 6 people found the following review helpful.
Excellent description of the data visualization design process!
By TULP interactive
Being a professional data visualization practitioner myself, I must conclude that Andy Kirk has really nailed it: the data visualization design process he describes matches my personal experience of creating data visualizations almost exactly. The book especially describes the process of designing explanatory and exploratory visualizations, and is less concerned with visualizations as exhibition.
I really like the chapter on Demonstrating Editorial Focus. This is something that is not often emphasized in data visualization introduction books, but it is a very useful one, as it focuses on the storytelling part of a visualization.
Chapter 5 provides a very good overview of different charts. If you're just starting out with visualization, you might see some charts that you didn't know before. If you're a real expert, you might be missing some, but the categorization nicely groups the different chart types by method. I especially like the fact that he mentions the appropriate data variables and visual variables, which is really helpful in picking the right chart.
Overall I think the book is very good, but be aware that the real emphasis is on all the aspects of the process itself. Don't expect a book with code examples on "how to create this visualization". So, when you've read this book, I think you're more aware of all the various facets involved in the design of a data visualization. You're also able to distinguish good visualizations from bad visualizations, and lastly, it gives you the right steps that should be involved in designing a visualization yourself.
The final chapter gives some great pointers to off-the-shelf software packages and visualization frameworks that you can use to design and construct visualizations yourself. The best advice is at the end of the book: Practice, practice practice!
5 of 5 people found the following review helpful.
Great process but why no color?
By Kevin Taylor
Enjoyed the book and found it to be a great way to organize the design process. Have done a lot of these things but seemingly unconsciously so this will be a great resource moving forward.
However, was more than disappointed with the exclusion of color in the printed version of the book. Counted at least 20+ references to color, including an entire section on color. Hard to follow a blue to red diverging scale in gray. Or the 3D pie chart that show up as 1 gray color, as if the 3D wasn't bad enough.
Again, I applaud the content of the book, just can't justify grayscale printing in ANY Data Viz book. Would have gladly paid $10 more to see examples in color.
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