Visualisation in data is about making it easy to identify points of interest within the data set. These could be trends, relationships, outliers and other KPIs. Because of this, it is always important to remember to make the marks on your visualisation easy to understand and hard to misinterpret. There are a few different ways to accomplish this in your workbook, but they can be broken into four key pre-attentive attributes. The most important attribute starts with positioning, then colour with size and shape at the end.

This hierarchy is due to pre-attentive processing. The process in which the brain filters all the information available and what is most important. While all are important for a good visualisation, each has its own situation to be helpful.

Position refers to 6 different points in particular:

  • Length
  • Width
  • Orientation
  • Enclosure
  • Position
  • Grouping

Colour can be broken into two different attributes:

  • Colour Hue
  • Colour Intensity

The last ones are

  • Size
  • Shape

 

To highlight the importance of these, I have attached a few workbooks that use the same data in different ways.

The worksheet that uses position is the easiest to identify which regions had the most profit. The one using colour is also easy to understand, but it still requires people to scan the information. The size chart is the most confusing as it’s challenging to identify which shapes are larger by looking.

This emphasises the importance of pre-attentive attributes in visualisation. Using the wrong pre-attentive attributes can be the difference between making an easily understood chart and a visualisation that can be misinterpreted.

If you have any questions feel to comment down below or reach out to any of DSAU16 team on LinkedIn!

Stephen Hughes
Author: Stephen Hughes