Becasue I often work with different kinds of practitioners, I often get questions like: How is this different from statistical methods, from Operations Research .... ? I was trained in earlier methods that often had the same goals, but with no claim of being a science. Just math and data based techniques that embed some useful goals and constraints. In prep for an upcoming presentation I reviewed the below to consider the differences. There are lots of overlap here, so you can't define them precisely. Often the best approach can be the one that your clients best understand. But its good to know and review the general direction of many of these. Also, hype does not mean right, and can confuse the issue when over-emphasized. Good piece. Join DSC for more.
16 analytic disciplines compared to data science in DSC
Posted by Vincent Granville on July 24, 2014
What are the differences between data science, data mining, machine learning, statistics, operations research, and so on?
Here I compare several analytic disciplines that overlap, to explain the differences and common denominators. Sometimes differences exist for nothing else other than historical reasons. Sometimes the differences are real and subtle. I also provide typical job titles, types of analyses, and industries traditionally attached to each discipline. Underlined domains are main sub-domains. It would be great if someone can add an historical perspective to my article. ... "
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