Data-driven play: The changing scope of data science and business analyst roles

Data-driven play: The changing scope of data science

Data scientists and analysts need to be thinking more in terms of play and conversation

Social skills are not, perhaps, the first words that many people would associate with data scientists . They are far more likely to be seen as geeks, communicating mainly with computers. But the world of data science is changing, if indeed that geeky perception was ever true. Nowadays, data scientists and analysts need to be thinking more in terms of play and conversation as ways to deliver insights into data.

The importance of play

The importance of play is a perennial topic in the ongoing discussion about improving education systems around the world. Children play naturally – first by themselves, and then with others – and this is how they first start to learn about the world. As adults, though, we “put away childish things” and may forget how to play, as well as the importance of doing so.

You can argue – and many do – that this is bad for our mental health, and that even adults need time to play. But I would take this further. I believe that adopting a more playful approach is essential in getting insights and value out of data. The Queen of Denmark takes time to do things that are actively not useful as a way to improve her quality of both life and work, and I think we could do a lot worse than follow her example. It is when we stray away from routines, and are not blindly focused on a target, that we find new possibilities and ways forward.

It is when we stray away from routines, and are not blindly focused on a target, that we find new possibilities and ways forward.

The history of scientific invention and discovery is full of happy accidents, from Marie Curie to Alexander Fleming. Taking a playful approach to your data increases the chances you will have a “happy accident” and uncover new insights.

Working together

One of the issues about play, however, is that it is better with a companion. Very young children play alone, or alongside others, rather than with them. They will often watch others and copy their games, though, and as children grow, collaborative play becomes more common. You can see how much more the children get out of their play by sharing ideas and coming up with new games together. It is, almost inevitably, the same for adults.

Collaborative working will get you a lot further than working alone – and collaborative working with someone different and unexpected may unearth whole new benefits. It is harder to work with someone new and unfamiliar, but the insights that emerge can be worth the effort. Most of us will be familiar with Belbin’s team roles, and the idea that you need different types of people to create an effective team. We also understand the idea that adding grit to the oyster is essential to creating the pearl.

Adding grit to the oyster creates the pearl. Collaborative working and play will get you a lot further than follow routines and working alone. #DataScience Click To Tweet

In data science, one very good way of adding a new dimension to exploring data is to bring together expertise in data science – and therefore in handling and exploring data – with expertise in the business – and therefore in what the data actually means in the real world, and the customer or business problems that need to be resolved. This can open up new worlds to explore, and uncover some really good insights.

You can add even more to the potential by including the data itself in the conversation, and letting it tell its own story. This may sound a bit fanciful, but I think that sometimes just looking again at the data from a different angle can give new insights, especially if you keep asking questions. You need to be thinking about what the data can tell you, and what you can learn from it all the time.

A collaborative culture

Working with others and with your data is a good start, but it is only a start. It is a good for individuals to start working together, but organisations also need to cultivate a culture of collaboration. They can do this by breaking down silos, and encouraging colleagues across domains to share insights and ideas. Routine communication across functions and domains encourages sharing of ideas, and the more that silos are broken down, the more likely this becomes.

As you start to think about how to get new insights into your data, it may be time to move away from having coffee with your colleagues. Instead, why not take a cup of data or ideas to your favourite analyst or business colleague, and start to generate information and insights?


About Author

Jeppe Deigaard

As an Advisory on Advanced Analytics and Business Intelligence I am aspiring to bridge gaps between tech and business. I am an Information Management professional specialising in Business Intelligence, Visual Analytics and Artificial intelligence.

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