Data Visualization Today
Many people in business have a rather jaundiced view of the function of graphs and charts. They see them as colourful but rather simplistic ways to convince others less familiar with the facts than they are themselves; whereas numbers written in a spreadsheet are somehow seen as being harder facts.
Maybe blocks of bold colour have a childlike feel as compared to the more serious and adult regimented rows of monochrome numbers. Whatever the reasons behind this line of thought, it is completely flawed and bad business sense.
Good data visualization can make or break your Business Intelligence system. All of the data collection and analysis must come together at some point if insight is to be reached and a decision made. With the right visualization, decisions appear to make themselves and this is exactly how it should be.
Regardless of the high esteem in which we hold our own abilities, we humans are not terribly good at retaining data in our short term memories – exactly the skill required when it comes to complex decision making. Scientific research into memory and visual cognition has found that working memory in humans is in fact extremely limited and as a result the manner in which data is presented can have a dramatic impact on our understanding.
In crude terms, let’s take the example of a series of numbers showing monthly sales results. Representing this data in a line graph will take up considerably less working memory than if the same data were presented as a table of numbers.
The importance of this in the workplace should not be underestimated as most business decisions will require a balancing act between many variables and the ability to hold several thoughts in mind simultaneously is essential.
Furthermore, it has been discovered that humans have an ability known as pre-attentiveness. This instinctive skill is what we do when presented with new information and occurs in those moments prior to conscious thought taking place. Through this we can detect size, colour, spatial grouping and the direction of movement; the skills humans would have undoubtedly used as hunter gatherers.
The research results show a priority in the speed and quality of human visual perception which helps to identify what constitutes both good and bad practice in the creation of data visualizations. Our ability to spot differences in length is greater than our ability to identify differences in area – this suggests that bar charts can be a lot more informative than pie charts for example. The choice of colour and the levels of complexity all play their part. So considering the role of visualizations is to make the data both understandable and memorable, the science would seriously question the use of some recently popular techniques such as the speedometer chart.
By taking these findings into the design of its visualizations, Tableau Software has cleverly managed to two kill two birds with one stone. Firstly, during the process of discovery – the analysis and interrogation stage – data is presented in exactly the ideal format to aid comprehension. This is critical as it keeps the user engaged and encourages the iterative progression from which the patterns, trends and relationship will emerge. Secondly, it uses exactly the same visualization techniques and understanding in its end product – the presentation slide or dashboard – and as mentioned above, it is those aspects of easy comprehension and retention that are so important in the support of decision making.
If you are interested to learn more detail about the visualization of data, there are many illuminating books in this field. Here are the names of a few that we would highly recommend - “Exploratory Data Analysis” (1977) by John Tukey, “The Visual Display of Quantitative Information” by Edward Tufte (1983) and “Show Me the Numbers” (2004) and “Now You See It” (2009) by Stephen Few.