I will be studying full-time for a 1-year MS in Business Analytics. What advise would you give to a person in this situation so that he can make the most out of his time out from work and get the maximum benefit from such a program?
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The biggest piece of advice I could give is to take a course in microeconometrics/labour econometrics as a part of your course. If your course coordinator wonβt let you, beg. If they still wonβt let you, then go off-line for a week or two and properly digest Mostly Harmless Econometrics (or if your stats isnβt too good yet, Mastering Metrics). If you want to go and work in health analytics, then replace what I just wrote with the equivalent for research design.
Why learn microemet? Basically, many of the big questions in business are of the form βwhat will happen if we do xβ. Predictive models that arenβt informed by causal reasoning do *terribly* at this questionβthey answer the question βwhat do we see happening to y when we see xβ. Inferring what will happen to y when you fiddle with x is a difficult task when all your data come from a world in which you did not fiddle with x. Too often we come across people with great technical chops who arenβt even aware theyβre making mistakes when answering these questions. Donβt be one of these people.
The second biggest piece of advice would be to not become too enamoured by the sexy end of data science (especially predictive algorithms), but *do spend the time learning this stuff in depth*. Often the simple stuff done well is far more useful to real-world decisionmaking.
Third: read very widely.
In my opinion, you should be thinking about looking for work. Try to network and see if there are employers were looking for analytics. This is different from analysts. They could be market research companies, companies are looking for pricing decisions, and even productivity.
Look to companies where the culture and business processes are not instinctual. Rather look for companies that require analysis.
Unfortunately, one becomes more Bible as one becomes more familiar with the tools of analysis. This may be SAS, business objects, or any other reporting environment.
In conclusion, a massive degree in analytics should result in a job sooner or later.