As the lyrics to the multiple award winning song ‘The Real Slim Shady’ by American rapper Eminem, aka Slim Shady, echoes in my head, I feel like this could be the theme song for the Data Scientists in 2019 if you replace Slim Shady with Data Scientist…
“I'm Slim Shady, yes I'm the real Shady
All you other Slim Shadys are just imitating
So won't the real Slim Shady please stand up
Please stand up, please stand up?”
Why would I say this you might ask? The reason is that there are so many data professionals these days who call themselves Data Scientists and, honestly, who wouldn’t want to be called a Data Scientist? But… who are the real Data Scientists and who is just imitating?
Firstly, let's clear up a bit of a confusion around the titles, roles and the overlapping of some data professionals’ responsibilities, specifically looking at Data Engineer / Data Analyst / Data Scientist.
I read an article which I personally think defines the titles the best, they wrote it as follows:
- Data Engineer: a data professional who focuses on building data pipelines, manages how to get data from point A to point B.
- Data Analyst: a data professional who focuses on producing reports describing trends/insights in data.
- Data Scientist: a data professional who focuses on producing insights and predictions from data.
The author used the words "focuses on" in each description to show that these roles aren’t set in stone and could quite easily overlap from time to time, depending on the company, team structure etc.
Looking further into the Data Scientist, these guys and girls are of vital importance to take us into the AI-driven future we are all talking about and anticipating. They usually have more experience and skills than Data Analysts, especially along the lines of computational skills, to extract valuable actionable intelligent insights from data.
Coding is the gateway to an AI-driven future and Data Scientists are the gatekeepers who possess insane coding abilities and aren’t afraid of using them.
All qualified Data Scientists have these mentioned skills, but what separates the real Data Scientists from the rest?
It can be difficult to answer and to tell the difference between them. At some point in the future it will become easier to differentiate, because we will see the results which the various individuals, teams and organisations will be delivering. These experts will then most definitely be even higher in demand and companies will try and poach them even more than they are currently.
Knowledge, degree/certification and experience are not what allow the real Data Scientists to stand out from the crowd. What will indeed raise them above the rest are things like creativity, intuition, curiosity, perseverance, ambition to learn and develop daily, mastering, self-motivation and speed.
A Data Scientist should not be afraid of breaking things to discover and learn more about how they work, and what can actually be done to improve results, ultimately adding business value.
Data Scientists have a mastery of machine learning, statistics, analytics and artificial intelligence. Combined with these skills, you will have a true Data Scientist who cannot be stopped or put in a corner. They will be ‘sexier’ than ever and should to be appreciated, encouraged, given space to grow, rewarded and well-looked after as they will be on the radar of many organisations.
As a conclusion, I am by no means saying the Data Analysts who have all the needed qualifications and experience aren’t real Data Scientists, but there will be some differences and some will rise above the rest. Just like there was more than one Slim Shady, at the end there was only one real Slim Shady who stood up.
On the other hand, South Africa doesn’t have enough Data Scientists, Africa doesn’t have enough, the world doesn’t have enough yet, but there is most definitely potential and room for Data Scientists to raise up and stand up all over the globe.
