We’ve spoken at great length on the looming shortage of big data experts, about the fact that data scientists are going to be in shorter and shorter supply as more and more organizations realize the business value of unstructured data. In amongst all this doomsaying, however, we never actually stopped to think about what a Big Data Scientist is. What traits serve as the benchmark between scientist and enthusiast?
Clearly, there’s more to it than simply being analytical and logical. After all, the analysis of big data is a multi-disiplinary approach, encompassing a wide array of talents and a diverse skill-set. The personal traits of any successful data scientist will reflect this. So, with that in mind…what makes a data scientist?
They Are Analytical
The first, most obvious trait any data scientist needs to possess is the ability to analyze, quantify, and calculate. Big Data is extremely confusing, complicated, and complex. The simple act of determining which data-sets will provide insights is difficult enough on its own, let alone actually drawing out those insights once they’ve been isolated. The ability to mentally address these massive, chaotic data-sets is a valuable one, and speaks of a formidably logical mind. Of course, the ability to analyze this data doesn’t mean anything without the ability to arrange it in a way that’s conducive to it. That brings us to our next point…
They Are Organized
A large part of the challenge of big data is that it’s so hard to address through traditional computing infrastructure; so difficult to organize and arrange. Owing to this, data scientists need to possess incredible organizational skills if they’re to thrive. After all, you can’t really organize and arrange something complex if your mind – and life – are a disorganized mess.
They Possess a Creative Mindset
Now we’re getting into rough terrain. Data scientists need to be able to slip into a creative mindset with relative ease. The reasons for this are twofold: first, the insights that can be gained from big data aren’t always clear even after it’s been analyzed; nor is the best means by which an organization can utilize it. As a result, any data scientist worth their salt isn’t just logical and analytical – they’re creative, too.
They Have People Skills
Data science isn’t a solitary pursuit. The analysis of big data is more often than not the task of an entire team of individuals, all working in tandem to ensure that they can draw out the insights their organization is looking for. If that team is comprised of people who have no idea how to relate to one another, it will inevitably fall apart. Not only that, the very nature of big data demands a certain understanding of human beings in order for one to successfully work with it (more on that in a moment).
For these reasons, a big data scientists needs to be able to understand, talk to, and relate to others. If they’re unable to do this, they might not really be suited for the job.
They are Able to Communicate Effectively
One of the tasks of a data scientist is taking highly technical, complicated, and confusing insights and explanations and condensing it down so that it can be understood by individuals with no technical background. It thus goes without saying that a data scientist must be capable of effectively communicating their thoughts and ideas. They need to be able to explain and describe their job without launching into a highly detailed, arcane explanation of the science behind it. Communication skills are a must.
An Understanding of Social Media
One of the largest, most common sources of big data is the social network. Everything a user does on a website like Facebook – from sharing a video, to clicking on a link, to liking a post, to commenting on a status – falls under the umbrella of unstructured data. Without an understanding of the intricacies of that network – without an understanding of the ins and outs of it – how can a data scientist possible hope to work out which data is good and which is bogus?
They Know that Big Data is About The People Behind It
Ultimately, big data is created by people. Without people, there is no big data. This is a valuable insight which a great many organizations seem to forget: at the end of the day, you’re looking at what the data tells you about the men and women who created it. Yes, you’re going to use this information to adjust your business strategy and reorganize the way you to things, but at the same time, no data scientist should ever forget that there are real people behind every action.
They’re Patient and Tenacious
Again, this one is a given. Analyzing anything as obtuse and expansive as big data requires a great deal of patience, discipline, and determination. Your data scientist could have the sharpest mind in the shed, and a glowing personality to go with it, but if they don’t have the patience to apply those talents, then they’re effectively useless. They need to strength of will to spend what might amount to hours looking for a correlation which might not even exist. Not everyone possesses such patience, so not everyone is suited to the job of data scientist.
They’ve the Technical Background
While looking at all these other qualities, don’t forget that you should be looking at what your scientist knows, and what they have experience with (though this is arguably the least important quality – programming languages and application interfaces can be learned, after all). Ideally, they should have a background in IT or a similar field, and possess a basic working knowledge of Apache Hadoop and MapReduce, in addition to being familiar with at least a few programming languages.
They Are Willing to Explore
Last, but certainly not least, your ideal scientist should be possessed of a deep, driven curiosity. They should always be on the lookout for a new method of analysis, always searching for a new insight, always seeking out a new correlation. A willingness to explore – and learn – is an oft-overlooked trait of any successful tech professional, but that doesn’t make it any less valuable to have.