Like all the best concepts in business, data visualization is nothing new. In fact, when I say it’s nothing new, I really mean that… there is absolutely nothing new about the fundamental principles of data visualization.

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When our prehistoric ancestors daubed crude maps on cave walls to show the rest of the group where the best hunting ground was, they were harnessing the same concepts and principles as we utilize today when demonstrating worth to clients, or when presenting end of year reports. It is only the methods and the levels of refinement which have changed.

Growing Sophistication

Of course, when we think of modern data visualization we are approaching the subject with a little more complexity than those early pioneers. Modern data visualization is about more than just presentation. It is about defining and identifying insight and connecting data with those who need it most, and in the ideal configuration. It is about telling stories.

There is evidence to suggest that data visualization in a refined form existed as early as the second century CE. It was probably in use even before this, but it was not until the Enlightenment period and the 17th century that the sophistication of data presentation really began to grow.

French-born polymath Rene Descartes was a celebrated author, philosopher, mathematician, physicist and astronomer, so it will be of little surprise that he was a mean data visualizer as well. His work with data visuals would be an important foundation stone for the work of Scottish mathematician, William Playfair, around a century later.

Playfair’s innovative graphs, which displayed progression over time, and his charts, which showed proportions of a whole as pieces of a pie, became massively influential and are still used today. You’ve probably used one yourself fairly recently.

New Data for a New Era

When William Playfair (1759 – 1823) was alive, data was changing. In fact, everything was changing – the United States broke free from British rule, in France the ruling royal family were usurped in a bloody coup, and across the world, entrepreneurs were making a killing in burgeoning industries. As you might imagine, in this tumultuous world, data was becoming increasingly important.

Events in Washington and Paris ushered in a new form of governance; one in which ultimate power was not locked behind the gates by an elite few and in which accountability was key. Private factories and industrial regions were clanking into life across Europe and the United States. The captains of industry at their helm also found accountability – to investors, shareholders and customers – to be the order of the day.

It is here that we see the beginnings of moves towards modern data forms and concepts, the first glimpses of governments and industrial practices that seem familiar to us even to this day. There was much work to be done of course – and a lot of progress to be made in refining and developing data collection and presentation methods – but the building blocks were already well and truly in place.

Twentieth Century Trailblazers

By the time we reach the 20th century, data has already grown in importance but the democratization process is far from over. At this point, data and visuals were still in the hands of the elite statisticians – worlds away from the masses.

So, how did we make the leap? How did we get where we are today – ready and willing to deliver top quality data and insight directly to people from all walks of life?

The work of the French mapmaker, Jacques Bertin, certainly helped to push data visualization forward. The award-winning cartographer was one of the first to recognize how the striking visual power of a map could be harnessed within the presentation of data.

Leading statistician, John Tukey, pushed the envelope even further in 1977 when he developed the approach of exploratory data analysis. While working as a professor at Princeton, Tukey began to work on ways to make sense of large amounts of data, and to gain better insight from these data masses. In doing so, he advanced the science of visualization.

Moving into the 1980s, ’83 saw the publication of the early data visualizer’s bible, The Visual Display of Quantitative Information by Edward Tufte. Tufte, along with Tukey and statistician, William Cleveland, were the figures who really began to refine what we think of as data visualization today.

Later on, the work of Stuart Card, Jock Mackinlay and Ben Shneiderman helped to hone this process further, giving us the techniques that we rely on today. Thanks to these visionaries, and those that went before them, we now have the power to gain and demonstrate insight in new and increasingly exciting ways.

So… What Does It All Mean?

How does this relate to the landscape of modern data visualization? What does it mean for us, working in the here and the now, to give our content users, our investors and our customers the data they need, when they need it?

Well, it shows that data visualization is far more than a simple flash in the pan – a trendy buzz phrase for media marketers and entrepreneurs to drop into conversation. Instead, it is a technique – or range of techniques – with history and depth, with a long background of trial, error, refinement and development.

The infographics, interactive applications, timelines, data maps and node diagrams that we create today represent the pinnacle of centuries of work. We are at the cutting edge of an exciting and ever evolving system of communication. It is up to us to build upon the work of those who went before us, moving it forward into an exciting tomorrow.

How data visualization will evolve in the coming years is difficult to predict. The appetite among individual consumers and among businesses for the latest technological gadgets, platforms and concepts is huge. This is driving technology forward.

We have already witnessed data visualization keeping pace with technological leaps – adapting to smartphone devices, sophisticated rendering software and accelerated internet connections with relative ease. Whatever lies around the corner – wherever the data takes us – it is sure to be an exhilarating ride.

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