How To Work Through A Problem Like A Data Scientist
Last Updated on August 15, 2020
In a 2010 post Hilary Mason and Chris Wiggins described the OSEMN process as a taxonomy of tasks that a data scientist should feel comfortable working on.
The title of the post was “A Taxonomy of Data Science” on the now defunct dataists blog. This process has also been used as the structure of a recent book, specifically “Data Science at the Command Line: Facing the Future with Time-Tested Tools” by Jeroen Janssens published by O’Reilly.
In this post we take a closer look at the OSEMN process for working through a data problem.
Work Through A Problem Like A Data Scientist
Photo by U.S. Army RDECOM, some rights reserved
OSEMN Process
OSEMN is an acronym that rhymes with “possum” or “awesome” and stands for Obtain, Scrub, Explore, Model, and iNterpret.
It is a list of tasks a data scientist should be familiar and comfortable working on. Although, the authors point out that no data scientist will be an expert
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