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Monday, August 31, 2020

Platforms for Data Science

Good piece in O'Reilly about this question,  largely-non technical and useful thoughts. Passing it on ...

Why Best-of-Breed is a Better Choice than All-in-One Platforms for Data Science
All-in-one platforms built from open source software make it easy to perform certain workflows, but make it hard to explore and grow beyond those boundaries.

By Matthew Rocklin and Hugo Bowne-Anderson,  in O' Reilly 

Do you buy a solution from a big integration company like IBM, Cloudera, or Amazon?  Do you engage many small startups, each focused on one part of the problem?  A little of both?  We see trends shifting towards focused best-of-breed platforms. That is, products that are laser-focused on one aspect of the data science and machine learning workflows, in contrast to all-in-one platforms that attempt to solve the entire space of data workflows.

This article, which examines this shift in more depth, is an opinionated result of countless conversations with data scientists about their needs in modern data science workflows.  ... " 

(Much more at the link) 

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