A few months ago I was really excited at the prospect of getting to see Cole Nussbaumer Knaflic talk at a local meetup co-organised by the Data Science Melbourne and Melbourne Data Visualisation groups. Unfortunately, Cole was sick that night and was unable to attend! Luckily for us, we have plenty of her ideas and advice to process in her book Storytelling with Data, as well as her wonderful blog of the same name.
Storytelling with Data is a fantastic introduction to data visualisation for those looking to improve their ability to effectively communicate with data, providing an abundance of tips, tricks, and best practises. It takes a minimalist approach to covering the vast and sometimes daunting field of data visualisation, with each chapter concisely covering a core concept, together with relevant references for those wanting to dig deeper. The logical sectioning of the subject matter into easily digestible chunks makes the book an enjoyable read cover-to-cover, or an great “quick reference” guide when seeking tips about a specific visualisation challenge. Chances are, if you’ve prepared a chart and want to spruce it up, a quick look at the relevant section of Storytelling with Data will provide you with numerous things you can immediately try out, likely taking your chart to the next level in terms of aesthetics and effectiveness!
What really makes this book stand out as being beginner friendly and therefore accessible to a broader audience of burgeoning data visualisers(?!) is the fact that every visualisation included in the book was created using (the ubiquitous) Microsoft Excel. Even better, she has made the actual Excel files available for download from storytellingwithdata.com! With an increasing variety of complex tools available for creating data visualisations – from open source code-based solutions like D3 or R’s ggplot, to licensed “out-of-the-box” software like Tableaux or Power BI – the recognition that a poorly designed visualisation will be limited in its effectiveness regardless of the tool used to produce it, is quite refreshing. In this way the book achieves its goal of providing design considerations from a high level, while being backed by rationale based on scientific principles of visual perception and human cognition.
Unlike many voices in this space, Nussbaumer Knaflic doesn’t claim to be a source of objective truth, and instead positions her suggestions as just that – suggestions; she’s not afraid to debate this belief in a public forum either, as evidenced by the now infamous “Great Comment Section Debate” of 2016 between her and another prominent data viz expert Stephen Few regarding the use of stacked bar charts. She went on to expound on her philosophy in a separate post on her own blog, the core idea of which I believe is summarised in the following quote:
“I believe that data visualization sits at the intersection between science and art. There is absolutely some science to it: best practices and guidelines to follow. But there is also an artistic component. This means that two different people may approach the same data visualization challenge differently. There is room for diversity of thought and approaches.” – Cole Nussbaumer Knaflic
In summary, for those seeking to extract more meaning from any data they have at their disposal – or even just hoping to minimise the mental or cognitive effort required of the audience, be it stakeholders, clients, customers, or even your bosses! – Storytelling with Data will be an invaluable resource. It’s accessibility and general-purpose approach means that the concepts provided will be useful for people at any level of an organisation, and across a range of industries. With books like this, there are no longer any excuses for showing bad, ugly, or wtf data visualisations again!
Bonus! For those in more technical or scientific fields I can also highly recommend the book Trees, Maps, and Theorems by Jean-Luc Doumont. Although now a decade old, the discussions are similarly high level and tool agnostic, focusing on core principles of perception in how visualisations are interpreted and processed.
