Recently the job
title of "Data Scientist" has
become en vogue.
Just like the buzz
word "Business Intelligence" has evolved from previous concepts, the
function of "Data Scientist" is hardly new. In fact, on of its
predecessors, "Statisticians", had the aura of being dull & boring, back when
being a geek was not chic. So we needed a
new title to justify it suddenly being cool?
Language in social
context can be a funny thing. All the more ironic that many challenges in
business intelligence and data analytics these days revolve around semantics
and ambiguity of source data, the very phenomenon that humans seem to
intrinsically create.
It also seems
convenient how suddenly an army of consultants, tool vendors and job seekers
smoothly morphed their existing portfolio and previous experience into being
"Experts" in Business Intelligence
or , well, "Data Scientist". In the end, I find my friend
Jeff's self-titulation as "Data Archeologist" cooler.
To be fair, what
emerges under this new moniker of Data Scientist is an amalgamation and
refinement of previously distinct disciplines, such as Business Analyst,
Database Administrator, Software Developer, Statistician, etc. Yet, Information
Science (not to be confused with Computer Science) has always concerned itself
with topics just now hitting the lime-light in terms of desirability in
businesses. The primary factor for the role of Data Scientist going viral may
just be businesses' realization that there is money to be made with insights
into the data exhaust from our business processes and social interactions on
the Internet. The classic, "you build it and they will come". Now
that this mass of data is available, we might as well use it, and "oh wow,
you can actually monetize all this?!".
My hunch is that the
role of an analytical and data integration specialist will eventually fade into
an expected subset of skills in the modern knowledge worker, both as individual
contributors as well as managers. If you look at how much responsibility over a
broad range of complex decisions the average white-collar worker has these
days, it is as if they were running their own business within the larger
organization, with information tools and all. So it would make sense that
eventually, between tool simplification, data-integration automation, and
commodity-pricing of related products/services, "data science" will
be yet another expected business skill set, such as fluency with Microsoft
Office products and PCs has become the norm over the old business standards 30
years ago.
