What qualities does a successful analytics professional have? T-shaped skills. But, we are getting ahead of ourselves. Let’s define a T-shaped person first.
Then, there’s a horizontal person with broad skills. In this case, this professional is a generalist.
A “T” shaped person has substantial depth in a field, but also understands the business. For example, the professional may know how to write code and which applications can improve employee engagement.
Now, of course, this isn’t a new concept. The business world has been talking about T-shaped developers for some time. This model has even been extended to a Pi-shaped developer or a comb-shaped developer, depending on the number of specialization pillars required. Nevertheless, the demand for T-shaped people is increasing again as analytics takes center stage in this increasingly digital world we live in.
We are rapidly moving from analytics practiced in isolated lines of business to a central organization that looks at the entire business holistically. For many leaders, the challenge is building a team that’s ready to handle the needs of that next-generation analytics function.
Most data scientists would advise that past data is one of the best predictors of future data. According to Crowdflower, an organization that reviews the state of data science annually, data scientists spend nearly 60% of their time cleaning and organizing data. What skills does this situation require from analytics professionals? Let’s have a look.
Six skills and a sixth sense
The foundation skills for analytics professionals do not call for much elaboration. Analytics professionals need a strong background in mathematics and statistics. You don’t necessarily need a PhD, but you should understand the basics such as normal distribution, probability computations, and sampling errors. A solid software engineering background is also required. I’m not necessarily talking about achieving a degree in these areas; however, these fundamental skills provide an appreciation of how good software is built, designed, and enhanced.
Next are certain traits. The first one is obvious: A pursuit of learning. Analytics is a rapidly evolving field, and if you stopped to rest, you are already a dinosaur. When you know how to get the right answers, you can start asking the right questions with a curious mind. And with all of this information, your love for storytelling – although underappreciated by most analytics professionals – can give your client or executive audience a perspective on what the data is saying. Most likely, they are not interested in your forward-backward algorithm or Hidden Markov Model. They just want to know what parameters will change buying behavior to decrease cart abandonment rates, for example.
The skills of an analytics professional form the inner core. A subset of programming tools might include:
- Knowledge in one programming language such as R, Scala, or Python
- Fluency in one data query or manipulation language – SQL being the most popular, but there are also PIG and HiveQL, among others
- Understanding of a good framework such as TensorFlow, Theano, or Caffe
By far, the toughest skill to achieve is intuition-based domain knowledge. I would go one step further to say that, more than a skill, it’s a sixth sense. Amy Wilkinson, author of “The Creators Code,” talks about entrepreneurs as sunbirds – people who transfer ideas from one field to another. Such a skill comes from a thorough understanding of not just one field but related fields. And in our brave new digital world, this perhaps best describes what next-generation analytic professionals require not just to survive, but also thrive!
For more on how digitial transformation is changing business, see Live Business: The Digitization of Everything.