Big Data Is As Much About Aesthetics And UX As Analysis

To move ahead, data needs to be both useable and beautiful


Data is here, and it’s here to stay. If you’re still talking about the data revolution then you’ve already missed it. Companies who haven’t yet adopted a data-driven approach are so far behind their competitors as to be either inconsequential or out of business. It has changed the way that companies operate. A prime example is in marketing, where only 10 years ago data was barely on their radar, whilst according to a report from Jaywing, 92% believed that data management is a key priority for their business today. It is a huge swing and is true across practically every area of most companies, from the warehouse to the board room.

The reason for this speed is down to an increased understanding of data amongst a wider segment of society. Today, it is everywhere - we even have analyses of 45 minutes of soccer that looks at a larger number of data sets than the average CEO would have done when making a business critical decisions 10 years ago. People now understand both the importance of data and how to understand it. However, this understanding goes only as far as reading the analysis, not how data was collected or analyzed beforehand. This is broadly true whether you are the CEO of a multi-billion dollar company or somebody watching a baseball game in a bar.

It is why data in 2017 is as much about aesthetics as it is analysis.

Data visualization is what has allowed people to understand what they’re seeing; you couldn’t simply provide a spreadsheet with the same data and expect it to be understood. This is not a surprise. According the Social Science Research Network, 65% of the population are visual learners, meaning they understand things easier if they can see them in a visual form, rather than reading or hearing something. It means that when data is visualized in an aesthetically pleasing format, people are more likely to understand it. This is why traditional graphs have gone from being bland, grey printouts to interactive and colorful pieces of art. As we live in a society with almost everything designed to grab our attention, we need critical data displayed in a way that does the same.

The practice is constantly evolving too and how people display data is one of the defining features of whether people are likely to either trust what the data says or become a customer of the company. Today, presenting data in a poorly laid out or dated way is the equivalent of submitting a proposal in comic sans with a word art title.

However, data visualization and the understanding of data by an audience is only part of the reason why aesthetics and UX are essential to data. With the current data skills gap, where there is predicted to be a shortage of 1 million skilled people by 2021, companies are increasingly turning to Big Data as a Service platforms, where they are essentially giving the ability to analyze data to those who are less data literate. It may not be as effective as having fully trained data scientists, but the reality is that it at least gives companies who would have no access the opportunity to use data effectively.

One of the major elements of making these platforms a success is the ability to make them as easy as possible for people to use, which means not only do they need to be powerful, but they also need to be useable. It’s why UX is so key to the increased use of data in the future; unless these platforms are both powerful and useable, people will simply turn away from them.

We can look back at how Windows revolutionized personal computing for a comparison, with 1992 being a watershed because Windows 3.1 created UX that was easy enough for the majority of casual users to operate. Where previously trying to use a computer was only for those who understood coding and could operate it through MS DOS or similar command line based systems, Windows 3.1 created a graphical interface that allowed people to undertake computing functions, but without the ability to program. It is similar to what we have seen with web design in recent years, with people now having the ability to create websites without knowing how to code, with simple visual interfaces like Wordpress and Squarespace. The sites created look great, even if they are not as powerful as something created by a trained web developer.

This is the approach we need to be take to data, we need to make it beautiful and understandable when it’s analyzed and easily analyzable through effective interfaces and UX. It is an easy goal to set, but a considerably more difficult one to achieve.


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