In the Data Visualisation Rush

Data volumes which can be easily produced and accumulated nowadays are enormous but revealing their advantages is harder than ever. What we still need is complex and erratic information to be presented with clarity, efficiency and precision. For this purpose, we have a variety of data visualisation tools at our disposal, but in a rush, we can easily slip into vivid visualisation effects and lose benefits of the systematic approach of working with data.

Therefore in anticipation of lifting Flexmonster Pivot Table Component to a new level, we start a series of weekly blogs about data visualisation. We will go all the way through often neglected basics to everyday tips for making your visual communication better. Let us start with a quick review of three key principles of the qualitative data visualisation.

First of all, any visualisation present data simply by showing it and by inducing the viewer to think about the substance rather than about design, used tools or methodology.

Secondly, large data sets must be coherent. By presenting many numbers in a small place information could become available at several levels of detail, from different perspectives which encourage the eye to compare diverse pieces of it.

Lastly, qualitative data visualisation serves a reasonably lucid purpose. It can be exploration, description, decoration etc. Thus, it must be synchronised with the description and be eliminated of any possible distortions and flaws (Edward Tufte, 1983).
As ordinary as they may sound mentioned aspects can be easily disregarded while working with large data sets. You probably have met these flamboyant visualisations which can be really hard to understand, inconsistent dashboards, or unnecessary infographics.

So do you want to see a good example?

For your inspiration here is a classical work of William Playfair (1759-1823)[1], a Scottish political economist, the founder of graphical methods of statistics, one of the pioneers in time-series visualisation using economic data.

Here the author plotted three parallel time-series: prices, wages, and the reigns of British kings and queens[2].

As a conclusion, while working on your visualisation message think about your client who longs for insights not only for impressive visualisation. Let your data reveal its hidden story in the most simple and beautiful way. In the next posts we will tell you how easily Flexmonster Pivot Table & Charts Component can do that, so stay tuned!