18.5 Syntax is Temporary, Concepts are Forever

As an analytics professional, it is important to know your way around the coding environment that you’re using, and to also understand the underlying processes.  Of course, the question of “code or stats?” is not an either-or, as knowing both of these comes with the job description.  That said, if you absolutely had to pick one area to emphasize?  

Coding environments will change with time. You may even have to adapt to a new programming language, interface, or software when you change jobs. The beauty of this is that the learning curve will not be steep for someone with a solid foundation in statistical concepts. You will know what to look for to solve a business problem. So do not agonize over whether to learn Python or R, Power BI or Tableau. Focus on the statistics, and everything else will fall into place.

If you spent your summer internship using Tableau, but just found out that your dream company uses PowerBI exclusively?  Do not panic.  You will still be in the running for the job. Here’s why:

If we were hiring an analyst, we would be much more interested in whether the person knew when to use a scatter plot, as opposed to a barplot, rather than whether the person knew the steps for generating either one in some particular statistical environment.  You will take to PowerBI, Tableau or any other software like fish to water if your statistical fundamentals are strong.