Data science is the science of insights which is as much an art as well. Effective usage of algorithms is, no doubt, one of its prominent features but it’s not restricted in that. If we reflect at the epistemology of this subject, we cannot undermine its empirical nature as a science. Our evolving need to meaningfully leverage the data-explosion – which is a companion of digitisation - is prime responsible for creation of this subject. When we require taking a risk based on such new category of information – rigorous mathematical steps are necessary but not sufficient. An intuition about how we are reaching to certain conclusion is very much an imperative. One aspect of any empirical subject is that it is open to inter-disciplinary influences and its boundary is a permeable one. I want to share that view here with some reasons in its support.
What I am calling here as “intuition” is technically an inter-disciplinary reference – to understa