Data visualisation is emerging as a hot (or cool?!) tech topic - it's starting to gain momentum and demand attention from the mainstream press, vendors, consultants etc. I just watched a great TED talk on the subject by David McCandless - his choice of data sets (global spending, facebook status etc.), and the metaphors he uses to describe the benefits and potential of visualisation really help to convey the opportunity that effective visualisation yields when dealing with seemingly overwhelming volumes of data.
Yet I believe data visualisation alone is not enough.
Great pictures certainly help, and David's bespoke infographics are very effective at conveying his message, but they face two problems:
- Custom infographics require specialised skills and a lot of time and effort - even simple images like the 3 triangles above don't just roll off the pen or screen (if they are accurate)
- Static images introduce the reader to a subject, perhaps inform the reader of a few key facts, but can't convey a detailed story; every engaged reader will be intrigued by the image above, but want to know more... a good visualisation will raise more questions than it answers
The first point is best addressed by generic data visualisation applications which, whilst they can't produce truly bespoke infographics, can - and do - provide a wealth of customisable visualisations which reduce both the graphic design / artistic skill set required, and the time and effort expended, in creating powerful visualisations - three of the best such applications are listed here on this website.
To deal with the second point, however, we need to look beyond visualisation alone and consider how interaction allows the reader to explore data landscapes and uncover surprising insights.
Interacting with data forces us to consider software applications again - we can't interact with a complex infographic if it was created by hand (whether by pen or graphics tablet). To interact with data effectively we need a rapid response - ideally instant - so that we can alter the visualisation according to our investigation of the data.
The best software applications allow us to move between different 'layers' of data (from macro to micro, and back again), different subsets of data (between countries, categories, time periods etc.) using multiple visualisations at the same time to allow the reader to examine the data from several angles at once.
Such interactivity encourages exploration - 'wandering' through a data landscape, admiring views, following paths, considering options and engaging with the information present. Exploring data in this way leads to an appreciation of its complexity, unlocks hidden patterns which testify to subtleties of similarity and difference, and leads the explorer to understanding and insight - the ultimate goals of all 'business intelligence' environments.
So I propose that it is interactive visualisation that offers the greatest potential benefit when attempting to understand and act upon our ever-increasing volume of information.