Data visualisation is big right now. A couple of years ago this term was hardly known, and we simply created graphs, charts, maps and dashboards as needed without a great deal of fuss. Today there is a plethora of software products and web services that allow us to create these same entities but with every bell and whistle imaginable – 3D, embedded graphics, animated, designer color schemes, interactive etc etc. The central question is whether this adds real value, or whether it is just blingware.
The answer to this question depends on why we might use sophisticated data visualisation software in the first place. If it is to simply get at the facts then there is a good argument to say that less is more and over the top visualisation is an unnecessary distraction. Making real use of data requires much more than visual inspection of attractive graphics. Elaborate sales charts say nothing about the significance of the numbers, I’m afraid that only statistics will tell you that particular story. A five per cent drop in sales for a product group may not look good on a chart (depending on the politics behind the construction), but five per cent may be well within the variation experienced over the lifetime of those products. Every picture tells a story – but is the story accurate? So for meaningful analysis of data for detailed factual information it is likely that visualisation may detract from the story in the numbers.
On the other hand data visualisation is often used to achieve a political end largely divorced from the facts that are buried in the numbers. Attractive graphics, favourable representations of data (more on this in a minute), and easy conclusions can be achieved with most data visualisation tools. In this context it is quite fair to say that data visualisation is nothing more than blingware. Whether bling is useful in your organisation is for you to decide.
It is well known that the graphics used to represent data can paint widely different pictures. Representing numbers as the radii of circles for example effectively squares their differences. How an axis is scaled can exaggerate or diminish differences – and so on. Plenty of room for deception
As with every technology fad, data visualisation will diminish in its appeal and just become part of the furniture. But for now bling is in.