Thinking the Science in Data Science

Evocative piece:

The scientific method to approach a problem, in my point of view, is the best way to tackle a problem and offer the best solution. If you start your data analysis by simply stating hypotheses and applying Machine Learning algorithms, this is the wrong way.

By Rubens Zimbres, Data Scientist & Machine Learning Researcher.

Lately I’ve seen a lot of hype surrounding -- and lots of newcomers to -- the Data Science field. But what exactly is SCIENCE in Data Science? The scientific method to approach a problem, in my point of view, is the best way to tackle a problem and offer the best solution. If you start your data analysis by simply stating hypotheses and applying Machine Learning algorithms, this is the wrong way.

The picture below shows the steps necessary for scientific research, corresponding data analysis and simulation. In fact, it is a sketch of what I did in my PhD thesis. In a few words, I studied the past 27 years of Business Management literature and I tried to develop an epistemologically disruptive approach to measure and predict service quality, mixing Business Administration with Electrical Engineering concepts. Over the course of 4 years I performed quali-quantitative longitudinal research and developed a simulation using Agent-Based Modeling to try to find a 5 State Cellular Automata rule that could mimic human behavior. I approached Complexity concepts, self-organizing systems, emergence of order, and social networks. .... "