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CDO Challenges – Look a little closer… The essential skill of data visualisation

This edition of CDO Challenges delves into data visualisation. By mastering the art of data visualisation, data leaders can deliver hard-hitting pieces of evidence to non-data professionals in a way that is digestible and resonates with their aims.

Why is this needed? 

There are four main reasons why data visualisation is required:

  • Improved storytelling
  • Improved accessibility
  • Relationships can be seen
  • Improved exploration and collaboration 

One of the most treasured skills mentioned regularly by DataIQ members is storytelling. Data visualisation is instrumental in improved storytelling as it levels the playing field for the audience and draws upon basic human traits to make its point. People are inherently drawn to colours and patterns – this is true in clothing, art and culture – and data is no exception to this rule. By using colours and patterns, data professionals can add a new dimension to their storytelling capabilities to ensure engaged and receptive audiences. 

Information is only as good as the skills of those that receive it, so it is key for data professionals to make their data findings as accessible as possible to the widest audience. In business it can be difficult to regularly find time to meet and go through each specific point, particularly with key decision makers, which makes having a tool such as data visualisation essential as it can portray complex data in a simple and effective way. In addition to the speed benefits of data visualisation, it takes something complex and turns it into something more palatable. The stereotype of data being lists of numbers on a spreadsheet still exists, which is a deterrent for non-data professionals to learn real-world data skills; however, with the use of data visualisation, this hurdle is much easier to overcome.  

One of the main skills for a data team is to spot patterns. This is especially true for data professionals working in retail where there are frequently cycles of customer behaviours and the key to success is to be ahead of the curve. Data visualisation makes it easier for data professionals and non-professionals to spot relationships and patters within data sets. When presenting this information to non-professionals, it is usually most clearly identified through the use of charts and graphs which can be easily and rapidly understood by those who are still on a data literacy journey.  

Finally, the more accessible data is, the greater the chances of undertaking successful business opportunities as data-led decision making becomes easier. This means businesses can undertake new exploratory routes with their customer offerings with a much lower risk of lost investment. Furthermore, different departments can collaborate closer and more frequently as there is a lower barrier to entry when considering data literacy capabilities, so teams can spot areas of collaborative development more easily with informed actionable decisions.  

Be aware 

There are negatives to data visualisation that data professionals need to acknowledge. In a sick twist of irony, the message can often be easily lost instead of heightened. The human eye is naturally drawn to colours and patterns – which is ideal for a bright, fun chart – but the essential information must be easy to identify and not lost in the noise. 

If you were demonstrating something with multiple datapoints using visualisation, it can become very easy for viewers to make inaccurate assumptions about the meaning of the data. This can be down to the core information being lost or perhaps just poor design leaving viewers confused. 

The creator of the visualisation must also be aware of inherent biases being portrayed. It is very easy to draw focus onto the data you want people to notice and hide other pieces, but this must be avoided. The purpose of data visualisation is to make data accessible and understandable to those who do not handle data regularly – and that includes the data that can be embarrassing or against your objectives. 

It is worth ensuring there is a short explanation of the data and what people should be looking for. Frequently, visualisation methods can cause people to assume correlation and causation depending on the context and design of the document.  

Finally, the process of visualising data can be a time-consuming process. One of the major benefits of utilising data is that it improves speed and efficiency, so it is essential that the amount of time spent on generating visualised data is kept to a minimum to not undo the hard work already achieved.  

Data visualisation is one part of a multi-faceted toolbox that becomes wider data literacy. Without data visualisation implementation, businesses will struggle to gain speed and enthusiasm from non-data teams that are expected to improve their own data journeys. By being able to condense large data sets into something that is pleasant to view but also informative, data leaders will develop momentum for their data literacy and data culture programmes for their wider organisation. 

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