Why Creativity is Crucial in Data Science

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Data science might not be seen as the most creative of pursuits.

You add a load of data into a repository, and you crunch it the other end to draw your conclusions. Data in, data out, where is the scope for creativity there? It is not like you are working with a blank canvas.

For me, the definition of creativity is when you are able to make something out of nothing. This requires an incredible amount of imagination, and seeing past the obvious headline statistics to reach a deeper conclusion is the hallmark of a great Big Data professional.

Many of the most successful people come across as innovative thinkers when they have interviews with us. They have no choice, moulding the data in unique and unexpected ways is their job. Just as Einstein found inspiration in his violin playing, many leading data scientists find that when their creative juices are flowing, they often find the most elegant solutions to the challenges that they face. These Data Creatives are some of hardest to find candidates – mainly due to the subjectivity involved. (See also a previous blog for more on Data Creatives)  

It is actually one of my favourite interview questions:

“What is the …

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