Q18: Can you please talk about recent developments in higher education on how to train more analysts?

The past couple of years have seen some remarkable developments in higher education in regards to analytics. Just a few years ago there were only a handful of colleges and universities in the U.S. that offered any kind of degree in something akin to data science. However, now you can find dozens of schools offering graduate degrees in analytics and/or data science. These changes in higher ed were preceded by several vocational schools and certificate programs. All in, if you do a google search on data science or analytics degree program you will get 100’s of schools in your results.

Besides the U.S., I have seen a few program in the UK and several in India getting more into analytics education. In the Philippines several schools have already started implementing the CHED (Commission on Higher Education) memo requiring schools to offer a business analytics elective series of classes. We have come a long way in a short time, but what is best for you?

If you are thinking about getting some formal education you will need to determine where you are currently with your analytics skills and where you want to be long term. Because of the crazy growth in the field, it can be pretty hard to tell what is the best bang for your buck.

Without pointing to any specific institution or program, I can give you some broad difference to consider. In a latter blog I will actually review some of the best programs and talk about them in on my blog site.

So here are the differences as I see them:

  1. Accidental Analysts. People who are doing a lot of analytics and have for some time, but have no formal training in analytics. These are accidental analysts who still make up a huge % of people doing analytics every day. For people at this level, going back to school full time to get a formal degree is not generally an option. For people in this bracket short term training programs and certifications in specific tools are the best bet to stay on the cutting edge.
  2. Legitimate Data Scientists. Few and far between, people with both the academic credentials and the business experience to do significant data science generally look upwards to getting a masters or even doctorate in a specialized field from a top school. There are a lot of programs out there to do that, but they tend to be pretty expensive and difficult to get into.
  3. Aspiring Data Scientists. If you are still young in your career and/or not finished with college you can consider getting your undergraduate degree in a related field and then progressing on to post graduate work. This is a recent development that poses an opportunity to those just starting out. In the near future these kinds of analysts will replace the accidental analysts for the most part. That is if there are ever enough.
  4. Part Time Analysts. People who do analytics or are part of a data science team, but have already established a career path in a different discipline. For those like you, training programs and certifications abound. It is pretty easy to find one that fits your unique situation and give you the added data muscle you need in your job.
  5. Managers of Analysts. If you are not really the one doing the heavy data lifting, but have team members that do. You need to be able to understand them, but not all the things they do, then you might be looking for a more generalist overview of analytics. Trying to optimize your analytics business culture and lead big data projects are skills you might want to improve on. There are training programs popping up for this need as well.

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So where does this take higher education? Some schools and programs are very broad based and offer generalist solutions. Others are quite specific and are geared to producing specialists. Knowing which education option is best for you is the challenge.

Higher Education across the globe is evolving to incorporate more analytics and data science into its curriculums. The need is there and is growing at a break neck pace. Where we are now is lights years from where we were two years ago, but where we need to be is far down the road.

More on that next blog post. In the meantime, if you are trying to figure out how to up your analytics game, drop me a note and I’d be happy to help you figure out what path you should take.

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