The 3 Levels of Data Science Awareness

With all the talk about Data Science and A.I., it’s easy to forget about the person doing all this and how his awareness grows as he gets more involved in the field of data science. What’s more, all those gurus at the social media will tell you anything about data science except this sort of stuff, since they prefer to have you as a dependent follower rather than an autonomous individual making his own way as a data scientist.

So, as you enter the field of data science, you are naturally focused on its applications and the tangible benefits of it. As a professional in this field, you may care about the high salary such a vocation entails or the cool stuff you may build, using data science methods. Everything else seems like something you have to put up with in order to arrive at this place where you can reap the fruits of your data science related efforts. It’s usually at this level of awareness that you see people complain about the field as being too hard, or not engaging enough after a while. Still, this level is important because it often provides you with a strong incentive to continue learning about this field, growing more aware of it.

The second level of data science awareness involves a deeper understanding of it and an appreciation of its various tools, methods, and algorithms. People who dwell in this level of awareness either come from academia or end up spending a lot of time in academic endeavors, while in the worst case, they become fanatics of this or the other technology, seeing all others as inferior, just like the people who prefer them. The same goes with the methods involved since there are data scientists who swear by the models they use and wouldn’t use any other ones unless they absolutely had to. This is the level where most people end up with since it’s quite challenging to transcend it, especially on your own.

Finally, when you reach the third level of data science awareness, you are more interested in the data and the possibilities it offers. You have a solid understanding of most of the methods used and can see beyond them since they all seem like instances of the same thing. Your interest in data engineering grows and you become more comfortable with processes that are either esoteric or mundane, for most people. Heuristics seem far more interesting, while you begin to question things that others take for granted, regarding how data should be used. The best part is that you can see through the truisms (and other useless information) of the various “experts” in the social media and value your experience and intuition more than what you may read in this or the other book on this subject.

It’s fairly easy to figure out which level you are in, in your data science journey. Most importantly, it doesn’t matter as much as being aware of it and making an effort to move on, going deeper into the field. Because, just like other aspects of science, data science can be a path of sorts, rather than just the superficial field of work that many people make it appear. So, if you want to find meaning in all this, it’s really up to you!