On academia and data scientists


“It is not the strongest of the species that survives, nor the most intelligent that survives. It is the one that is the most adaptable to change.” --Charles Darwin

The more that I learn about the topic of Big Data, the more I'm amazed at the current and future skills gap. Data scientists are in hot demand and we're just not printing them fast enough. The Big Data train has left the building. The world needs more data scientists, and lots of them – at least according to consulting outfit McKinsey.

It turns out that some colleges and universities recognize the need to change their curricula, and sooner rather than later. Count among them my alma mater, Carnegie Mellon. The school offers a number of Big Data and analytics elective courses, including one that I'd take in a heartbeat today called Very Large Information Systems:

This course studies the theory, design, and implementation of text-based information systems. The Information Retrieval core components of the course include important retrieval models (Boolean, vector space, probabilistic, inference net, language modeling), clustering algorithms, automatic text categorization, and experimental evaluation. The course covers a variety of current research topics, including cross-lingual retrieval, document summarization, machine learning, and topic detection and tracking

Go Tartans! Now, to be fair, CMU is among a number of schools that have been at the forefront of information management and technology for quite some time. Count CalTech, MIT and RPI among them. Still, to play in this sandbox means that school administrators and department heads have to constantly adapt. The course described above is not your freshman calculus course. Not too many people were talking about Big Data even two years ago.

A Different Mind-Set

Contrast that type of mentality with what you find at many schools – good schools, even. Stodgy administrators and committees sit in their ivory towers, unwilling or unable to recognize emerging trends. They remain steadfast in their decision-making, rarely altering courses or tracks to reflect new changes. Classes must be based upon tried-and-true theory and those with industry experience are seen as somehow less valuable than pure academics.


Ultimately, this mind-set hurts students who deserve to learn about important recent trends and thinking. To those stuck in their ivory towers, remember that your entire raison d'être (doubly true in many professional programs like MBA, MIS, etc.) is to educate students and help them get jobs. Period.

Simon Says

If educational institutions want to keep charging exorbitant fees, they had damn well better make sure that the squeeze is worth the juice.


What say you?


About Author

Phil Simon

Author, Speaker, and Professor

Phil Simon is a keynote speaker and recognized technology expert. He is the award-winning author of eight management books, most recently Analytics: The Agile Way. His ninth will be Slack For Dummies (April, 2020, Wiley) He consults organizations on matters related to strategy, data, analytics, and technology. His contributions have appeared in The Harvard Business Review, CNN, Wired, The New York Times, and many other sites. He teaches information systems and analytics at Arizona State University's W. P. Carey School of Business.


  1. Great post Phil!

    I'm thinking that perhaps we could take the "Very Large Information Systems" together, now that would be awesome...

    From my perspective, not only do universities need to start getting on board, organizations need to start re-training their staffs to start learning these technologies, similar to the way they did when organizations started transitioning from mainframes to open systems.

    I know that the IAIDQ (International Association for Information and Data Quality) folks were trying to keep track of "data management" opportunities at universities but I’m not sure what happened to that.

    About 2 years ago I wrote about opportunities for education in data management here on the Data RoundTable and I pondered "what to do next". Well, here I am two years later still wondering what to do, I think it’s time to "start squeezing some juice".

    All the best...Rich

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