A few years ago, a political party in India tweeted a particular bar chart that a lot of you may not have forgotten. The chart depicted fuel prices over the years. The last bar in the chart was the smallest of all, but the amount corresponding to it was the largest in the entire group. At first impression, it looked like fuel prices were cut sharply that year, but in reality, that wasn’t the case.

This chart was called out by many, but meanwhile, it managed to leave many confused. That chart was a good example to show what one shouldn’t do while visualising data.

Why would you talk about that chart when the book Impactful Data Visualisations: Hide and Seek With Graphics (part of IIMA business books series) has nothing to do with it, one may wonder. That’s because the book shows you more examples of wrong visualisations.

Much more than words

But the author also takes the effort to tell you what went wrong with a lot of visualisations and what can be done to rectify them. That is one major reason why a data enthusiast must read it. It clearly tells you what to do and, more importantly, what not to do with data, while visualising it. In fact, the book begins with a few of these examples, which keep you hooked to it.

There is absolutely no point in writing a data story or presenting a data-backed report and forgetting the way to visualise the numbers. This is because visuals convey messages about numbers with so much ease, in a way that words cannot.

Also, they cater well to short spans of attention. The book talks about various ways to visualise data, prompts one to think beyond the usual lines and bars and use them in a much more effective manner.

The author not only walks you through various ways of visualising data but also tells you what is best suited to represent what kind of data. But that’s not all the book is about.

It also talks about ways in which data visualisations can manipulate you. For instance, there is a chapter titled ‘The deception of the third dimension’ and another called ‘Spurious trends and how to read them’. It would take you less than half an hour to read these chapters and they will in all probability, blow your mind.

The last chapter, ‘Tell your data story’, deals with yet another important aspect. It lets one decide how to tell their audience, the most important part of the graphic and make them understand the insight that the author had in mind. She lists out attributes like colours, shapes, sizes and borders.

In fact, most data researchers or journalists wouldn’t have thought of a few simple solutions that she lists out here. These solutions can be easily adopted by newsrooms too to make their graphics more understandable to the readers. The chapter ends with a few exercises to spot data manipulation and practice solutions.

Given its subject matter, the book leans towards the academic side and may tend to get a tad boring at some parts, but the author has made an earnest effort to make it as interesting as possible.

If you possess a genuine interest in data and aspire to pursue a career in the field, reading this book is highly recommended.