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> So, contrary to its name, data science is rarely science. That is, in data science the emphasis is on practical results (like in engineering) - not proofs, ma

> So, contrary to its name, data science is rarely science. That is, in data science the emphasis is on practical results (like in engineering) - not proofs, mathematical purity or rigour characteristic to academic science. Science in a nutshell is to take a hypothesis, test it rigorously and validate/invalidate the hypothesis based on the results. The results of this experiment could be extremely practical. Data science that follows the scientific experimental design, does science. The one that doesn't is equivalent to reproduction of past experimental results OR putting a blindfold on your eyes and throwing darts around until it hits the bull's eye.

stared 9y ago
I disagree with this common, yet faulty, explanation. (IMHO coming from people who have never worked in science and for whom everything R&D looks like "science!".) Building engines or cars (involving a lot of tests!) is considered engineering. And as any serious engineering it's not purely random trails&errors. A/B tests are not a sufficient criterion to make something science. And data science (in business) is focused on solving practical problems (which may or may not be research) rather than open-ended research (which may or may not be practical). Source: I worked in academia. I now work in data science. You?
- denzil_correa 9y ago
  I have a Ph.D in Computer Science and I have worked across research labs in the industry too so I very much understand where you come from. That said, I don't see the disagreement between us and what part of my explanation you found faulty.
  - stared 9y ago
    Sorry for being combative. It comes from two things: - giving talks at universities (then I admit that "data science" is more engineering, compared to academic science) - people who had only experience with software development and then any research-like stuff (or simple mathematics) suddenly becomes "science!"

stared 9y ago

I disagree with this common, yet faulty, explanation. (IMHO coming from people who have never worked in science and for whom everything R&D looks like "science!".) Building engines or cars (involving a lot of tests!) is considered engineering. And as any serious engineering it's not purely random trails&errors. A/B tests are not a sufficient criterion to make something science. And data science (in business) is focused on solving practical problems (which may or may not be research) rather than open-ended research (which may or may not be practical). Source: I worked in academia. I now work in data science. You?

denzil_correa 9y ago
I have a Ph.D in Computer Science and I have worked across research labs in the industry too so I very much understand where you come from. That said, I don't see the disagreement between us and what part of my explanation you found faulty.
- stared 9y ago
  Sorry for being combative. It comes from two things: - giving talks at universities (then I admit that "data science" is more engineering, compared to academic science) - people who had only experience with software development and then any research-like stuff (or simple mathematics) suddenly becomes "science!"