Show, Don’t Tell
The final stage of the data analysis process is to communicate your insights. Data analysis is about turning raw data into information and knowledge. Knowledge is information people understand and can act on, so communicating the information in your data to people is a crucial part of the process of turning it into knowledge.
Data by itself is difficult to consume. Even well-organised tabular data is hard to read when you have more than a few rows, as you have seen from working with Aisha’s data. One of the best ways to make data easier to understand and to spot patterns and trends within it is to visualise it.
People are generally able to recognise and compare size, shapes and colours more quickly than they can numbers, because humans are very good at spotting patterns in visual information. Data visualisation takes advantage of this natural ability. Visualisations can be as simple as a line chart, showing how a value is changing over time, or as complicated as a series of 3D, colour-coded animated maps showing statistics on a global scale.
One of the most famous data visualisations ever created was a map. In the early 19th century, nobody understood how the deadly disease Cholera was spread. During an epidemic in London in 1854, a doctor called John Snow mapped Cholera cases, and noticed they were clustered around the centre of Soho. He used the map and other statistical methods to prove that the disease was spreading from a single pump, which was contaminated by sewage. His evidence meant the handle of the pump was removed, and deaths prevented. His discovery led to wider public health reforms that saved many lives.
When you’re presenting data, you should also consider how you use it to tell a story. Stories help people contextualise and remember information better, and can lead people through the reasoning behind your recommendations or insights.
Journalists are using data to help them tell stories in new ways. Some of these are both entertaining and enlightening, like Neal Agarwal’s visualisation of the Deep Sea. But some stories can be about relating abstract data in powerful, real terms. The maps produced by the Guardian newspaper in 2019 to make the scale of the Australian bushfires comprehensible to people in other countries are a great example of this. You can explore these yourself via the link in the See also section.
In a business context, the stories you tell should be about what the data says, and what that means for the company. You are presenting evidence to help people take action, so consider structuring your presentation with a three part narrative and a call to action:
We can see this data is behaving like this… which means… so we should do….
For Aisha, a visualisation could help her spot opportunities for her business. If she plots the postcodes from her customer data on a map, she can see that she has very few deliveries to Clifton, an area to the north east of her shop. But if she looks at this area on a map that shows the relative affluence of the population, she can see it’s a wealthy area. There could be an opportunity for her to expand into a new, lucrative market.
If you communicate your insights well, you can persuade people to change their opinions, and take action.
Take your learning further
Designers Stef Posavec and Giorgia Lupi spent a year visualising their lives on postcards
A Map of the Index of Multiple Deprivation for the UK
To see Aisha’s (fictional) location, search for BS1 4DJ.
Have your say:
- Has this video changed the way you think about ‘boring’ graphs?
- Can you think of any other great examples of data visualisation?
Share them in the comments.