Search the internet for Data Visualization and you will come across many different definitions of what it is and an equally large range of products. Whilst there are many self-proclaimed "experts" on Data Visualization there is very little material that you could call concrete.

The first milestone in Data Visualization is usually considered to be William Playfair's Commercial and Political Atlas published in 1786. Look at it now and you would be hard pushed to see much difference in the presentation of much of the data with the modern day - with the exception of the elaborate text. Along the way there have been some outstanding works which have literally revealed the life saving truth found in data, for example the work of Dr. John Snow. Edward Tufte has largely been credited with writing the books that have shaped discussions on Data Visualizations in the present day. His work has led to many of the limted number of innovations we have seen over recent years such as sparklines and small multiples. Others such as Stephen Few and Rolf Hichert have made valuable contributions to the increased awareness of Data Visualization techniques.

Our expertise lies in the hard earned experience of real projects. Whilst there are earnest debates going on about the best colour or the most suitable format and what the data to ink ratio should be, ultimately there has to be a business case behind a Visualization. That business case might be pure analysis - we have these number, what do they mean? It is unusual however to just be given a broad brief, usually we have a number of competing goals - I have a story to tell but I only have a short time to make my point.

Data Visualization is not a science and it isn't an art. Somewhere in between we have to be able to find some common ground where everybody is happy. Having sat in a number of workshops where people have asked questions like "what's the best colour for a line" or "how should my dashboard be laid out" its obvious that people would like some rules. Whilst it would be easy to say that we can arrive at these by analysis, real world experience tells us that some people just don't like blue or that cultural considerations dictate whether the most important item should be on the left or the right of the dashboard.