As you might expect, “analytics,” broadly defined, was the star of virtually every presentation during the recent 2019 INFORMS Business Analytics Conference in Austin, Texas, with one notable exception. Interestingly and ironically, the “a” word never came up in the opening plenary panel discussion, according to a longtime INFORMS member who pays attention to these things.
By all accounts, moderator Noha Tohamy and panelists Viju Menon, Katherine Rosback and Nada Sanders were excellent, and they collectively presented the packed ballroom with a lively, informative session on “How Data Science is Revolutionizing the Future.”
So why little or no mention of “analytics”? One word: semantics. When I hear the word “analytics,” I envision a universe of different fields of interest, different industries and different practitioners, researchers and academics loosely united by the concept of data-driven decision-making. Data science and data scientists are prominent members of that realm, as are operations research and operations researchers, decision science and decision scientists, you name it.
At the moment, “data science,” however you define it, appears to be desirable – particularly for those looking to hire and those looking for jobs – so it’s not surprising to see erstwhile “data analysts” and “data miners” rebranding themselves as “data scientists.” I realize there are technical distinctions between them, but “data science” currently gets you quicker in the door.
Analytics magazine seeks to cover the entire spectrum of analytics, no matter what you call yourself. As we said, it’s mostly a matter of semantics, right?
Not exactly. Problems arise when people without a substantial background in mathematics or statistics start running around selling themselves as “data scientists” or “operations researchers” without the education, technical chops and experience to back it up. That muddies the field for bonafide, well-qualified analytics professionals.