The Citizen Data Scientist

Mike Guilfoyle of ARC has been doing some interesting writing on predictive analytics. One of the terms he uses is the “citizen data scientist.” I like the concept and will explain Mike’s thinking in this article.

But let me provide a little context first. It would be easy for a supply chain executive, or any business manager, to ask what is the difference between “predictive analytics” and “forecasting.” Forecasting is based on traditional mathematical and statistical models; predictive analytics uses machine learning, artificial intelligence (AI), and other advanced analytics to predict/forecast the future.

Author: Steve Banker


1 reply »

  1. It’s important for the Citizen Data Scientist to be able to check that the answer to a question he asks is not actually an answer to a different question.

    Algorithms written in Executable English help to avoid that trap, and also explain their answers step by step all the way down to the data used.

    There’s a platform for this online at with many examples. Try writing and running your own examples too !

    If you are reading this, you already know English, so that’s at least half the learning curve!


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