Dashboards are extreme data visualizations
In the recent Information is Beautiful 2014 awards, I found interesting that there is an infographics and a data visualization categories. My interpretation is that the entries in the infographics section are static and illustrated, while those in the data visualization are generated and data-driven. However, all the featured data visualization projects are about a one-off dataset. So aesthetical choices of the visualization depend on the characteristics of this particular dataset. By contrast, the dashboards I have worked with are about a live, real-time datastream. They have to look good (or at least – to function) whatever the shape and size of the data that they show. The google quote and news chart that we saw earlier must work for super volatile shares, for more stable ones, for indices, currencies, etc. So, if the distinction between infographics and data visualization makes sense to you, imagine that dashboards sit further in that continuum than data visualization. Not only are dashboards generated from data, like data visualizations, but they are also real-time and should function with datasets of many shapes and sizes.
But dashboards problems are not data visualization problems
Data visualization provides superior tools and techniques to present or analyze data. With libraries and languages dedicated to making visualizations, there is little that can’t be done. In many successful visualizations, the author will create an entirely new form, or at least control the form very finely to match their data and their angle. Even without inventing a new form, there are many which have been created for a specific use, and which are relatively easy to make on the web (as opposed to say, in Excel): treemaps, force-directed graphs and other node-link diagrams, chord diagrams, trees, bubble charts and the like. And even good old geographic maps.
In most cases, it is not a good idea to be too clever and have a more advanced form.
Up until mid November 2014, Google Analytics allowed users to view their data using motion charts.
This was really an example of having a hammer and considering all problems as nails. Fortunately, this function disappeared from the latest redesign.
Likewise, on twitter followers dashboard, the treemap might be a bit over the top:
and possibly confusing and not immediately legible to some users. On the other hand, it is economical in terms of space and would probably work in almost every case which are two things that dashboards should be good at. So while I wouldn’t have used it myself I can understand why this decision has been made.
Dashboards are not an exercise in visual design either
A dashboard such as this:
(for which I can’t find the source. I found it on pinterest and was able to trace it to this post but not prior) is well designed visually, it makes proper use of space, colors and type, its charts are simple.
But what good is it? what do I learn, what can I take away from it, what actions can I perform?
Most of the dashboards examples I find on sites like dribbble or beyance (see my Pinterest board) fall into that category: inspiring visual design, probably not real data, no flow, no obvious use.
Dashboards are problems of their own
What makes a dashboard, or any other information-based design successful, is neither the design execution nor the clever infovis technique. Dashboards, eventually, are meant to be useful and to solve a specific problem.
How so? We’ll see in the next article: dashboards as products.