In this article, we will explore some key issues, things to consider as well as practical tips for visualising survey data.
My submission is a simple curved bar chart with insights to clearly show the top benefits of remote working. The curved bars are a nice way to show the data in a modern style without compromising accuracy.
The takeaway here is that different designs can be adapted to show the required insights. Leading to more accurate decision making.
Changing the frame and focus helps tailor the visualisation to appeal to different internal, external or strategic audiences.
Colour and words are therefore a quick and easy way to highlight one of many potential insights from the data.
By using interactive features such as dashboard actions we can reveal hidden insights all within the same dashboard!
In my approach I use interactive parameters to drive the analysis, allowing users to select different measures.
A challenge social research analysts quite often face is how to effectively communicate data which will inform the solution to a particular social problem or issue. Decision makers quite often feel over whelmed by the wealth of information available. We need to reduce the time it takes for them to understand an issue and make an informed choice of how to resolve it. How do we go from a list of numbers to a clear message, which can inform a business decision such as where to target resources?
We have seen how the human brain processes visual information through iconic, short and long term memory. Pre-attentive attributes such as colour, length and position are visual properties that are processed very quickly in the sub-conscious memory. As data visualisers we can leverage pre-attentive attributes to focus our audience’s attention to highlight key performance issues.
Building different views allows our audience to see different insights from the same data. This means being able to quickly ask and answer business questions. This is important to be able to see the underlying cause of problems. It also means that we can go exploring in detail different paths of analysis, which is a great way to engage our audience’s curiosity.
Quite often we will see data visualisations which try to stand out by using too much colour. The problem is that this can lead to cognitive overload as there is too much to process. Additionally when everything is the same colour then nothing really stands out.
One of the challenges of analysing data is dealing with imperfect datasets. For this week's #MakeoverMonday Challenge, I visualised the sleep patterns of Americans by age and gender over time. The data is interesting as it shows most Americans aged 15 and over are...
Analysing the data as aggregate bar charts and individual points on a line made me think about different ways I could improve my average step count.
Set actions are versatile: the metric calculation can be used to change the chart, title and colour of the measure selector!
By using colour and an insightful title, we can focus our audience’s attention to a key take-away.