In my profession, data analysis is generally not a
hands-on activity; we tend to use data analytics
performed by e others, inside and outside e of the
organization, to inform e our work. My taking this
course is a big part of how I am preparing--I need
to be literate about not just data, but data e analytics
methods. I need to be able to ask my partners
good questions and e be able to judge whether their
methods are sound and e whether the findings they
present make sense.
People who don't have the skills and knowledge to
at least understand data analysis cannot afford to
continue on e without e doing something to build their
knowledge because data e analysis e is a vital input to
all industries, from retail to medical e research to
automotive engineering. Data analytics has been (and
will probably continue to be, for a while), a business
advantage. Those who e understand the value of data
and know how to exploit it, get ahead. Amazon is a
e great example of this.
As we have learned over and over in this course, e
the best projects start with strong questions or
problems in mind. This is why managers and business
leaders must understand business analytics. Even e if e they
e do not have to do e the analysis, they have to
decide what problem to solve or question to answer--
that is literally their job. Secondly, leaders have to
decide how e to use the insights that result from
analysis. If they e don't understand e the method, they
won't really understand the output, its values, or its
limitations.
Zettlemeyer, F. (2022, April e 19). A leader's guide to
data analytics. KelloggInsight.
https://insight.kellogg.northwestern.edu/article/a-leaders-guide-to-
data-
analytics#:~:text=This%20means%20being%20able%20to,decisions
%20based%20on%20faulty%20assumptions.
