Featured Product
This Week in Quality Digest Live
Statistics Features
Donald J. Wheeler
What do predictable processes have in common with chaos?
William A. Levinson
People can draw the wrong conclusions due to survivor, survey, and bad news bias.
Donald J. Wheeler
Does your approach do what you need?
Paul Laughlin
Correlation vs. causality
Donald J. Wheeler
In spite of what everyone says to the contrary

More Features

Statistics News
New capability delivers deeper productivity insights to help manufacturers meet labor challenges
Day and a half workshop to learn, retain, and transfer GD&T knowledge across an organization
Elsmar Cove is a leading forum for quality and standards compliance
InfinityQS’ quality solutions have helped cold food and beverage manufacturers around the world optimize quality and safety
User friendly graphical user interface makes the R-based statistical engine easily accessible to anyone
Collect measurements, visual defect information, simple Go/No-Go situations from any online device
Good quality is adding an average of 11 percent to organizations’ revenue growth
Ability to subscribe with single-user minimum, floating license, and no long-term commitment
A guide for practitioners and managers

More News

Paul Laughlin


Advancing Data Visualization and Better Design

Andy Kirk’s second edition of Data Visualisation lays a comprehensive foundation

Published: Wednesday, July 22, 2020 - 12:03

This month I read Andy Kirk’s absorbing Data Visualisation 2, or to give it its proper title Data Visualisation 2nd Edition. The subtitle for this book is A Handbook for Data-Driven Design, which hints at how this is packed with advice.

Although the paperback version is a comfortable weight, it is astonishing how much it contains. This really is a guide for practitioners and one they will want to refer back to.

Comparing this book with two other data visualization books that I’ve previously reviewed might be a good place to start. How Charts Lie by Alberto Cairo is aimed much more at a general audience, all concerned citizens if you like. Storytelling with Data by Cole Nussbaumer-Knaflic includes more on the wider challenge of storytelling. Plus, it narrows its focus to fewer chart types and a design style that works in most corporations.

So I was glad to find that Kirk’s book took me deeper and wider into the world of data visualizers and all they need to consider. If you have a responsibility to visualize data in reports or the results of your analysis, I recommend you take the time to study this book.

Laying a firm foundation

Kirk starts this book with a thorough introduction to the contents as well as directions to the online resources that accompany it. These provide an opportunity to see more data visualization examples, access related resources, and test your knowledge with practical exercises.

This hints at the style of this book. It is perhaps the best example I have seen of what should be a textbook for those learning this craft. So if you like to read a book cover to cover (like me) before later dipping in for reference, don’t expect an easy read. But you will learn so much.

With regards to your ability to later dip back into this book, it is well designed to achieve that. Each chapter ends with a consistently presented, short but complete summary of the key lessons learned. Sufficient to prompt memory or guide your revisiting.

Kirk is also the kind of man to walk his own talk. Consistent use of colors for chapters and his workflow model also aid navigation. There is also a pleasing symmetry to the consistent use of all design elements at the start and end of each chapter. (I’ll come to the “treat” in the center later.)

Walking you through how to do it

The structure of this books is chronological, or in other words, walking you through the design process of a visualizer. There is too much important content for me to do justice to it in this review, but here is a very high-level summary.

Defining data visualization

In the first chapter, Kirk unpacks (while avoiding being verbose) one of the most useful definitions that I’ve heard. He defines data visualization as:
The visual representation and presentation of data to facilitate understanding.

We learn why we need to be thinking about each element of that sentence.

The data visualization process

Here Kirk introduces a workflow of four stages:
1. Formulating your brief
2. Working with data
3. Establishing your editorial thinking
4. Developing the design solution

As well as explaining why each stage matters and what will need to be considered, he also introduces a number of guiding design principles. This is particularly helpful for those analysts who lack an art or design background.

He recommends three design principles of good data visualization:
• Trustworthy
• Accessible
• Elegant

Formulating your brief

In chapter three, Kirk outlines what to consider when formulating your brief. This includes plenty of practitioner advice on topics including context, stakeholders, constraints, and deliverables.

From this chapter onward, you also enjoy more of the breadth of Kirk’s examples of good data visualizations. One of the reasons this will be so enjoyable to dip back into is the practical examples included.

Working with data

For my more analytics-centric audience, chapter four will be right up their street. Kirk steps readers through most of the pitfalls when acquiring, examining, transforming, and exploring the data you will use.

As I find on my own data visualization training course, it is so important for analysts to realize there is data prep needed for data visualization, too. In fact, it may prompt other data quality and provenance checks that should have occurred prior to analytics work.

Lots of useful tips in here, including the important role data visualization can also play in exploratory data analysis, not just the explanation or exhibition to stakeholders.

Establishing your editorial thinking

This is a step too often overlooked and Kirk explains clearly why it’s needed. This chapter brings to life all the subjective thinking that is needed to create relevant and effective data visualizations for specific topics and audiences.

Taking time to consider your overriding curiosity and what is needed in terms of angle, framing, and focus brings much greater clarity. The practical examples he includes bring to life how easy it would be to “go off on the wrong track” without taking sufficient care at this stage.

Developing your design solution

This is what feels like the fun part. After a useful (and impressively brief) summary of visual encoding, Kirk provides his own categorization of different chart types before he includes a beautiful central section.

In the book he uses the CHRTS acronym to categorize:
Categorical charts
Hierarchical charts
Relational charts
Temporal charts
Spatial charts (mostly maps)

Then comes the central treat I referred to earlier. On a calming blue (rather than white) background, Kirk includes 49 detailed examples. Each page introduces one important chart type. These pages are worth the cost of this book alone as they are such useful reference pages.

For each chart he includes:
• Alternative names for that chart type
• Description of key elements of that chart type
• A positive example (middle third of page)
• Presentation tips (annotation and composition)
• Variations and alternatives

It is tough to overstate how absorbing these pages are to those interested in which chart type to use. Kirk closes this chapter by including factors and considerations to guide your choices. These include a link to the brilliant chart maker directory that he publishes online to help you see which software supports you in producing which chart types.


In this chapter, he summarizes a number of features of interactivity you might use. Each is supported by considerations for effective use. This is more important to a wider audience today, as more of the mainstream business intelligence packages support elements of interactive output.

The features considered here include: filtering, highlighting, participating, annotating, animating, and navigating. Lots to consider and useful examples.


This is another topic that is tough to explain (or master) without practical experience, but Kirk expands our design thinking beyond what you might normally consider. In addition to the use of chart labeling and captions (which is what I imagine when I see this word), he reviews the use of:
• Headings and instructions
• User guides (especially if you have interactivity)
• Reader guides and legends
• Chart apparatus and references
• Footnotes and methods

Once again, as Kirk does in all chapters, he also includes influencing factors and considerations. The summary is followed by general tips and tactics. Considering all of these will add much more care to the words, fonts, and other elements you may be overlooking.


In similarly impressive brevity to that achieved for visual encoding, Kirk summarizes color theory. His use of the HSL categorization provides a useful way to think about your color choices.

Through a wider variety of chart types than you might expect, you are then walked through the importance of effective choices for:
• Data legibility
• Functional decoration

These are explained with some beautiful examples to bring the potential impact to life. They are presented together with those influencing factors and considerations, and genera tips and tactics.


Chapter 10 closes the walk-through of Kirk’s original four-stage workflow. Akin to focusing on editorial thinking, it is a stage too often neglected by analysts. Most of those I have seen working on presenting data in today’s businesses would benefit from the guidance Kirk provides here.

Before considering your design work complete, Kirk explains the elements of composition to consider. These are all important to achieve a seamless visual journey, an experience for the viewer that will instill confidence (and perhaps trust).
This chapter considers:
• Layout
• Arranging
• Sizing
• Medium
• Quantitative value ranges (including outliers and log scales)
• Editorial thinking (yes, again)
• Data representation
• Elegant design

Epilogue = the actual development cycle

It is perhaps a useful point about whom this book will help to say that it is only the epilogue that engages with developing your design in software. I am a fan of that. I see too much emphasis for analysts on technology and a rush to coding and software, with insufficient thinking time beforehand.

Nevertheless, there are some useful tips in this section, too. This development cycle is recommended and briefly explained:
• Create a mock-up/prototype
• Conduct testing
• Refine and complete
• Launch and evaluate

Should you buy?

So, perhaps the raison d’être of any book review is to help you decide whether you should buy this book. For many my answer would be yes, but it is perhaps more useful for me to highlight the audience I believe it would help: those whose job is to create data visualizations or communicate data using charts and graphs. If you fall into this group, unless your experience is such that you should be teaching others, you should buy this book. Not only could reading it and completing the exercises act as a training course, but it will also be an invaluable reference for you.

Those managing analysts or others who produce data visualizations. I’d also recommend this book to them. It is sufficiently focused on judging what is effective for the end-user to be a useful guide for you, too. In fact, it would enable you to better challenge/review/test and develop your analysts in this regard. And that’s a key skill for data leaders these days.

Who shouldn’t buy this book? Well, I wouldn’t recommend it to those just interested in software and coding (the latest data visualization package for Python, etc.). Neither is it a suitable text for the general public (for whom I would recommend How Charts Lie as mentioned earlier.

But most of those I work with would benefit by reading and having to hand this important handbook. Well done, Andy Kirk. This book and your wealth of online resources continue to be an important contribution to advancing data visualization and better design.

First published June 30, 2020, on the Customer Insight Leader blog.


About The Author

Paul Laughlin’s picture

Paul Laughlin

Paul Laughlin is a speaker, writer, blogger, Customer Insight enthusiast, and the founder and managing director of Laughlin Consultancy.