Book: 'Data Visualization: A Successful Design Process'

I'm thrilled to share details of my first book 'Data Visualization: A Successful Design Process' available to buy now.




Welcome to the craft of data visualisation: a multi-disciplinary recipe of art, science, math, technology and many other interesting ingredients. Not too long ago we might have considered the role of charting or graphing data as a specialist or fringe activity: it was something that scientists, engineers and statisticians did. Nowadays, the analysis and presentation of data is a mainstream pursuit yet very few of us have ever actually been taught how to do this well. Taste and instinct normally prove to be reliable guiding principles but they aren’t sufficient alone to effectively and efficiently navigate through all the different challenges we face and the choices we have to make.

This book offers a handy strategy guide to help you approach your data visualisation work with greater know-how and increased confidence. It is a practical book structured around a proven methodology that will equip you with the knowledge, skills and resources required to make sense of data, discover insights and portray those to others. It will provide you with a comprehensive framework of concerns, presenting step-by-step all the things you have to think about, advising when to think about them and guiding you through how to resolve your choices.

Once you have worked through this book you will be able to tackle any project – big or small, simple or complex, individually or collaboratively – with an assurance that you have an enhanced appreciation of all the tactics and guidance needed to deliver the best results possible.

The Story of the Book

In January 2012 I was approached by an Acquisitions Editor from Packt Publishing to develop an 80 to 90 page eBook on the subject of data visualisation and, specifically, about the process of designing a data visualisation. Packt are a prolific and fast-growing tech book publishers and their business model is digitally-focused (not just in terms of subject matter but also in publication output). Over the course of writing the book during 2012 it grew in size (largely through my own content-creep) and now exists as a 206 page eBook and printed book. The structure and content of the book is complementary to my data visualisation training workshops and in many ways they have helped informed each other.

Whilst the eBook was the primary target format the printed option emerged as an intended output format half-way through writing it. It is important to note that, whilst the eBook is produced in full colour, the printed book is published in black only. This is not an author decision, rather it is a policy common to all titles published at Packt and appears to be an increasingly standard practice for smaller publishing houses as they contend with the costs of printing and handling the transition of the industry towards a print and digital platform mix. Of course a printed book about data visualisation would be and ideally should be available in full colour but the benefit to the customer is that the price of the book is reduced quite significantly.

Packt have created an attractive bundle that allows you to buy both eBook and print book for a very reasonable sub-£20 (sub-$30) price. So, the best place to get the book will be direct via Packt's website. As at 1st August 2014 the eBook is available at £10.19 (€14.44, $15.29) with the print book/eBook bundle available for £18.99 (€27.99, $29.99). The book is also available on (print at $26.99, Kindle edition at $16.36) and (print at £18.61, Kindle at £9.64) as well as Barnes & Noble (print at $28.86) and on Safari Books Online.

Thank you!

It is a constant and pleasant surprise to hear of anyone who spends their hard-earned money on my book, I am immensely grateful to all who have or will do so. Thank you in advance if I don't get chance to do so in person or electronically at the time!

I was immensely fortunate to have secured the input of Alberto Cairo, Ben Jones, Jerome Cukier and Santiago Ortiz as my brilliant peer reviewers and their feedback was highly valued and advice extremely welcome. Thank you guys!

What people are saying review by Danny Dorling

BookReview3 review by Jan Willem Tulp

BookReview review by Kevin Taylor

BookReview4 review by Chong Lee Khoo

Amazon1 review by Anonymous


A review by Alberto Cairo (

It seems that every consultant in visualization and infographics feels the urge to hold one or more books under her or his arm at some point. Think of Tufte, Few, Robbins, and now Andy Kirk. Andy, who runs the VisualisingData website, has been very active in the past few years, speaking and conducting workshops in Europe and the US. His first book, Data Visualization: A Successful Design Process,* reads as a detailed distillation of the ideas that he presents in his courses. If you attend one of them, the book may work as a reminder of what you learned.

...This is a book for beginners, after all, as Andy himself has recognized. But professionals will stumble upon things to learn or to remember, as well.

A review by Ben Jones (

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.

Some of the comments on Twitter

Who is this Book For?

Regardless of of role, background, capability and experience, this book should provide useful and practical guidance to anyone who is looking to learn about data visualisation design and/or wants to optimise his or her techniques. The overall aim is for it to be something for everyone: you might be coming into data visualisation as a designer and want to bolster your data skills, you might be strong analytically but need inspiration for the design side of things, you might have a great nose for a story but don’t quite possess the means for handling or executing a data driven design. Additionally, you may never personally get involved in the data or design and have other motivations for learning about data visualisation - you might be a manager looking to commission work or coordinate a project team and want to successfully handle and evaluate the outcome a design process in a more sophisticated way.

If you are satisfied with the effectiveness and efficiency of your current design approach, it may not be for you. If you are looking for deep levels of theory, software and code tutorials, or a coffee-table book full of glossy galleries of inspirational work, once again, this isn't the book for you - there are others out there that serve that remit (check the 'References' page).

You don’t need to be a gifted polymath to get the most out of this book but ideally you will have reasonable computer skills (software skills but not necessarily programming for the scope of this text), have a good basis in mathematics, and statistics, in particular, and have a good design instinct. There are many other facets that will of course be advantageous but the most important trait is just having inherent curiosity to use data as a means of discovering and communicating understanding. This will be the key attribute to get the maximum benefit from this text.

You cannot master data visualisation by reading this book alone. As with most skills in life that are worth pursuing, to become a capable data visualisation practitioner takes time, patience and practice. However, through applying the techniques presented in this book, then learning and developing further from your experiences, you will enjoy a continued and successful process of improvement.


1. The Context of Data Visualization (21 pages)

Chapter 1 provides an introduction to the subject, its value and relevance today, including some foundation understanding around the theoretical and practical basis of data visualization. This chapter introduces the data visualization methodology and the step-by-step approach recommended to achieve effective and efficient designs. We finish off with a discussion about some of the fundamental design objectives that provide a valuable reference for the suitability of the choices we subsequently make.

  • Exploiting the digital age
  • Visualization as a discovery tool
  • The bedrock of visualization knowledge
  • Defining data visualization
  • Visualization skills for the masses
  • The data visualization methodology
  • Visualization design objectives

2. Setting the Purpose and Identifying Key Factors (23)

Chapter 2 launches the methodology with the first stage concerned with the vital task of identifying the purpose of your visualization: what is its reason for existing and what is its intended effect? We will look closely at the definition of a visualization’s function and its tone in order to shape our design decision-making at the earliest possible opportunity. To complete this scoping stage we will identify and assess the impact of other key factors that will have an effect on your project. We will pay particularly close attention to the skills, knowledge and general capabilities that are necessary to accomplish an effective visualization solution.

  • Clarifying the purpose of your project
  • Establishing intent: the visualization’s function
  • Establishing intent: the visualization’s tone
  • Key factors surrounding a visualization project
  • The ‘eight hats’ of data visualization design

3. Demonstrating Editorial Focus and Learning About Your Data (26)

Chapter 3 looks at the intertwining issues of the data we’re working with and the stories we aim to extract and present. We will look at the importance of demonstrating editorial focus around what it is we are trying to say and then work through the most time-consuming aspect of any data visualization project: the preparation of data. To cement the learning in this chapter we will look at an example of how we use visualization methods to find and tell stories.

  • The importance of editorial focus
  • Preparing and familiarizing with your data
  • Refining your editorial focus
  • Using visual analysis to find stories
  • An example of finding stories and telling stories

4. Conceiving and Reasoning Visualization Design Options (39)

Chapter 4 takes us beyond the vital preparatory and scoping stages of the methodology and towards the design issues involved in establishing an effective visualization solution. This is arguably the focal point of the book as we look to identify all the design options we have to consider and what choices to make. We will work through this stage by forensically analyzing the anatomy of a visualization design, separating our challenge into the complementary dimensions of the representation and presentation of data.

  • Data visualization design is all about choices
  • Some helpful tips
  • The visualization anatomy: data representation
  • The visualization anatomy: data presentation (color, interactivity, annotation, arrangement)

5. Taxonomy of Data Visualization Methods (40)

Chapter 5 goes hand-in-hand with the previous chapter as it explores the taxonomy of data visualization methods as defined by the primary communication purpose. Within this chapter we will see an organized collection of some of the most common chart types and graphical methods being used that will provide you with a gallery of ideas to apply to your own projects.

  • Data visualization methods
  • Choosing the appropriate chart type
  • Comparing categories
  • Assessing hierarchies and part-to-whole relationships
  • Showing changes over time
  • Plotting connections and relationships
  • Mapping geo-spatial data

6. Constructing and Evaluating Your Design Solution (23)

Chapter 6 concludes the methodology by focusing on the final tasks involved in constructing your solution. This chapter will outline a selection of the most common and useful software applications and programming environments. It will present some of the key issues to think about when testing, finishing and launching a design solution as well as the important matter of evaluating the success of your project post-launch. Finally, the book comes to a close by sharing some of the best ways for you to continue to learn, develop, and refine your data visualization design skills.

  • For constructing visualizations, technology matters
  • Visualization software, applications and programs
  • The construction process
  • Approaching the finishing line
  • Post-launch evaluation
  • Developing your capabilities

Sample Extracts

To give you a flavour for the style and content of the book, below are a couple of extracts presented in pdf format.

From Chapter 1: Discussing data visualisation objectives

The first excerpt is taken from 'Chapter 1. The Context of Data Visualization' and covers some general objectives behind data visualisation design.


From Chapter 4: Discussing the design choices relating to colour

The second excerpt comes from 'Chapter 4. Conceiving and Reasoning Visualization Design Options' and specifically relates to the section on colour. I have specifically chosen to provide this section for download due to the issues of the no-colour print format.