What Can Your Data Analytics Team Learn From Star Trek?

As anyone who's ever been part of a data analytics team will tell you, the search for insight into data can sometimes seem like a Star Trek-like voyage into the unknown realms of deep space. So what can Star Trek teach us about the way we interact with and explore our data?
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Andy Cotgreave, social content manager at Tableau Software, explains why a strong team ethic can ensure that you boldly go where no data analytics team has gone before

"Data: the final frontier. Yours are the voyages of the data analyst. Your five-year mission: to explore strange new datasets, to seek out new insights and new outliers, to boldly go where no analyst has gone before."

I'm paraphrasing, of course, a well-known refrain, from one of the most popular television series of all time. But as anyone who's ever been part of a data analytics team will tell you, the search for insight into data can sometimes seem like a Star Trek-like voyage into the unknown realms of deep space. So what can Star Trek teach us about the way we interact with and explore our data?

For the purposes of this exercise, let's look at the original series of Star Trek, which first aired in September 1966. One of the main reasons it's endured so long - through a succession of feature-length films and spin-off series over the years - is that it focuses on a clearly defined set of core values. Whether exploring issues of morality, ethics or politics, Star Trek has always provided a great example of how a team made up of very different personality types can work successfully as a unit. It's a value-system that viewers find it easy to relate to, and serves as a valuable reminder to anyone working in a team environment to tolerate differences, and work to find commonality in favour of the greater good.

It's an approach that any team would do well to adopt, but in particular, I'd suggest that the crew of the USS Enterprise embodies the ideal characteristics a successful analyst, or team of analysts, have. Here's why:

1.Mr Spock - Mr Spock personifies the need for data analysts to provide cold, objective analysis. The Vulcan's greatest asset is that he remains emotionally detached and logical. As a result, he is able to assess requirements on their own merits, prioritise correctly and ensure that the right questions are being asked. Behave like Spock when you need to understand your problem and gather data.

2.James T. Kirk - The fabled Captain of the Enterprise, Kirk's, courage confidence, and ability to take risks, is central to the ability of the crew's performance as a team. The same qualities are also highly valuable to data analyst teams. By being willing to lead by example, challenging the status quo and developing new ways of seeing data you can achieve results that might previously have been impossible in your organisation.

3.Leonard 'Bones' McCoy - The ship's doctor, McCoy is the voice of reason on the otherwise chaotic bridge of the Enterprise. Conscientious at all times and understanding of other people's needs, he embodies the need for data analytics teams to have empathy. It's an underrated quality that can be the secret to ensuring that your analytics meet the needs of the end-user.

4.Scotty - As the engineer, Scotty works behind the scenes, making sure that everything is running as it should be. You probably don't want to get as flustered or angry as he does, but you do need to be mindful that there's only so far your analytics tool or infrastructure can be pushed before things fall apart or become impossible.

So which member of the Enterprise most reflects you?

Of all the lessons to be learnt from Star Trek, diversity is the most important. If you're an individual analyst, you need to adopt all the characteristics explained above. If you have a team of analysts, it is only as good as the sum of its parts. What makes for a truly great team of data analysts is the ability to provide skills that complement other team members, and which help the unit to function as a whole - regardless of individual differences in personality or outlook.

By adopting this approach, I firmly believe data analysts have the ability to visit strange new worlds of data interrogation, to seek out new ways of analysing data, and interpreting results.

What other science fiction characters can teach something about effective analytics? Let me know your thoughts on twitter (@acotgreave)