A recent post on the E-group, followed by a timely article in the FT, raised the issue of data visualisation and how best to do it. A webinar on the subject has been suggested, but in the meantime we have put together a summary of thoughts and possible software solutions.
Information overload is a perennial problem for researchers – how to communicate chunks of complex data in an easy and simple to digest format. This is not a new issue – working in the second half of the 18th century, William Playfair is thought to be the founder of modern data graphics, and invented line and pie charts.
The problem is even more acute in modern times with more and more data being created in shorter time frames. Data are used by all businesses, but understanding what those numbers actually mean is crucial for business success. And behavioural economics theory tells us that we are not good at comprehending statistics – our inherent biases mean that we interpret data based on our individual experiences and prejudices text which can lead to us misunderstanding the figures or drawing erroneous conclusions.
So being able to consolidate a lot of data into something that is meaningful and has value is a vital skill for researchers moving forward. We are increasingly expected to go beyond the numbers by adding context, providing clarity and extracting additional meaning. The increasing use of visual representation of data in the media has changed expectations – we are now used to seeing statistics presented in a colourful and visually arresting way in the news and now expect this as matter of course in all dealings.
What is clear is that Excel and PowerPoint are beginning to fall behind the pack both in terms of speed of data manipulation and presentation flexibility. Yet in the past the only alternative has been ‘enterprise business intelligence’ software aimed at big data users and with a price tag to match. Using a graphic designer is also a good solution –but can add time and expense which are often in short supply on projects!
In response to this demand, the past few years has seen an explosion of new developments in the business analytics area, with an array of new software options available designed to analyse, visualise and exploit the data. Whilst the full versions can be more expensive to licence than Microsoft products, many offer ‘free’ versions of their software. Some require programming knowledge (D3, R) but others such as Tableau Public, Qlik, and Alteryx do not.
The recent E-group debate on the subject identified the following (quant) tools that our members have used and recommended:
The next stage is replicating the fundamental idea of engaging visual communication in the qualitative space – harder to do as there are no statistics to use as a starting point. Rather it is about creating a strong narrative and making the data emotionally and visually engaging so that people remember it. There are a number of books and 'ideas sources' out there – pininnterest is a good browse when looking for creative ways so showing informaiton. I also have 'Visual Storytelling' (Gestalten) which I use to spark off visual ideas.