ANALY ZE T H I S !
I do my best to train
them to think critically –
and wherever possible,
to utilize user-friendly
tools – to address a
variety of data- and
model-driven business
problems.
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these areas, and to keep innovating to deliver it.
2. “Automation will empower the data scientist to
empower everyone else at the company, and they’ll
need the help of software.” Automating the data
scientist role has been discussed ad nauseam
[4], but Furrier has a slightly different take on it:
Automation is essential so that these critical human
resources can be better focused on changing
managerial behaviors, rather than having so much
of their time consumed with managing data.
3. “The role of the data scientist plays an important
part in setting the tone for collaboration within an
organization, as these multidisciplinary problem
solvers will need to communicate clearly with
each other, as well as every other department.”
That is, if the more technically trained analytics
professionals can’t work well with less technically
trained professionals, an organization’s analytic
capabilities will fall far short of their potential.
Back here at USF, my colleagues in the MSAN program
have made the choice to emphasize the computational
and statistical aspects of analytics, which as expected has
led to incoming students and outgoing graduates who are
suited for very technical roles. My MBA students, however, do not have either the programming skills needed to
implement algorithms from the ground up or the inclination
to acquire them. Instead, their focus is on the business
rather than technology. Instead, I do my best to train them
to think critically – and wherever possible, to utilize userfriendly tools, which will be flooding the market for years
to come – to address a variety of data- and model-driven
business problems, while also working through data quality and management issues as needed. Given the welldocumented talent shortages, it is not surprising that both
A N A LY T I C S - M A G A Z I N E . O R G
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