The Evolution of Data Science

Recently I read this article about the statement that more and more data science tasks get automated. Isn’t that kind of funny in a way. The people who develop the algorithms are automating their own jobs. And in this way also opening the doors towards general acknowledgement and access into technology. Something called citizen data scientist came up as well in this article. According to Gartner  these people are the new innovators. The tooling invented by the original data scientist is getting more easy and accessible to the public for their own use. An interesting part of these citizen data scientist is the fact that they do the data science part as a part-time job. How did this arise? Lets see what the researchers at Gartner have to say:

Easy means larger scale?

“Making data science products easier for citizen data scientists to use will increase vendors’ reach across the enterprise as well as help overcome the skills gap. The key to simplicity is the automation of tasks that are repetitive, manual intensive and don’t require deep data science expertise.”  Alexander Linden, research vice president at Gartner.

Evolution of Data Science

“Access to data science is currently uneven, due to lack of resources and complexity not all organizations will be able leverage it.” For some organizations, citizen data science will therefore be a simpler and quicker solution their best path to advanced analytics.” Mr. Tapadinhas, research director at Gartner


In my opinion this is a natural way of evolution. The evolution of a job or tasks, as you will, into the public and accessible for everybody. We have seen this before in many different angles. Lets take for example the job of taxi-driver. If you ask met there were 3 phases. In the first phase only the rich and well educated people could drive a car and therefore a taxi. A couple decades later phase two came around. In this phase can we conclude that taxi’s are common good and everybody is capable of driving these taxi’s. if you have a license of course. The third phase is of course the introduction and disruption created by Uber.

You see the similarities? I know for fact that the world is short handed in data scientists. This is a well known statement. It is only a matter of time before the world educates a lot of people in this area of expertise such as the enormous growth in the taxi-world was. And finally there will be the public and they will take over as soon the technology is made available by the new Uber of data science.

What do you think?