This book on data visualization by Andy Kirk of goes beyond its promise – it not only outlines a successful design process, as the title suggests, it also delivers an overview of the field of data visualization, a summary of key techniques and tools, and references to a litany of helpful resources. Most importantly, Andy demonstrates the type of mindset needed to bring people of all backgrounds together in this burgeoning field: humility and open-mindedness.

A statesman for the field
This should come as no surprise to anyone who has been following Andy recently. Over the past year, Andy has been travelling around the world conducting 1-day training sessions on data visualization, so he’s had the opportunity to discuss this topic with more people than most. If anyone sees the big picture in this field, it’s Andy. Last year I spent some time talking with Andy after his first European tour, and we recorded our conversation, which you can listen to here.

A proven methodology
While conceding that the process of creating a data visualization can be iterative or even messy at times, Andy seeks to outline a “structured design approach” that will help a designer progress from an initial goal through to publishing and beyond into reviewing the final creation. This approach was utilized by Andy in creating his “The Pursuit of Faster”, which won honorable mention in’s Olympics contest of summer 2012, so he has used it with success. For those of you allergic to “process” in creative endeavors, have no fear – the process Andy outlines is anything but rigid.

Points I vehemently agree with 

In outlining his process, Andy makes a number of key points that I strongly agree with, such as focusing on the reader, applying “editorial focus” to tell the story, and being open to constructive criticism. Andy understands the need to achieve both form (aesthetics) and function (effectiveness), and gets the order right – make it work before you make it beautiful. Also, he talks about the need to respect “visualization ethics”, and to strive for accuracy. He doesn’t just talk about it, he gives a list of things to watch out for.  Andy encourages the reader to put their work out there, whether on a blog or an online forum somewhere, and to connect with others – an approach that has benefited me greatly over the past two years.

I’ve made some of these same points here, just not as articulately as Andy does in his book. These are sentiments I’ve seen expressed by others in the field, most notably Alberto Cairo, who was one of my fellow technical reviewers for Andy’s book. Alberto’s book “The Functional Art” was also published recently, and is a fantastic read.

Points that challenged me
There were a number of suggestions interwoven in Andy’s description of his process that I found particularly convicting, and essentially boil down to steps I often skip. Here they are:

  • Keep a notebook of project work – I haven’t done this to date, and regret it. What I do have is a record of the final product, and I’d like to see a record of my thoughts and steps taken.
  • Clearly articulate the project’s reason for existence and intended effect – many times I just dive right into a project without really specifying what I hope to accomplish with the end product, or what “success” would look like. These aren’t just helpful things to jot down, they’re foundational to any project.
  • Only use interaction if necessary – some of the best visualizations are static. I often find myself adding interaction when it probably isn’t needed. Some of my most shared projects aren’t all that interactive.

Final take-aways
Andy advocates an approach to data visualization that is balanced and comprehensive. He understands and appreciates the “gray” inherent the endeavor, and applies a level of diligence and attention to detail that is required to find a winning solution. This book by Andy is a must-read for anyone seeking to hone this particular craft as he clearly lays out the steps one must take on the journey, even if those steps won’t be taken in neat succession. The book left me with a long list of healthy reminders and questions to ask myself the next time I decide to tell a story with data, and ways to do get those questions answered.

If you’ve read it, feel free to leave a comment – I’d love to know your thoughts.