DevOps for Data Science –DevOps isn’t the Toolchain In this series on DevOps for Data Science, I’m covering the Team Data Science Process, a definition of DevOps, and why Data Scientists need to think about DevOps. It’s interesting that most definitions of DevOps deal more with what it isn’t, than what it is. Mine, as … Continue reading DevOps for Data Science – DevOps isn’t the Toolchain (But you still have to care about the tech)
I’m wading into treacherous waters here in my series on DevOps for Data Science. Computing terms often defy explanation, especially newer ones. While “DevOps” or Developer Operations has been around for a while, it’s still not as mature a term as, say, “Relational Database Management System (RDBMS)”. That term is well known, understood, and accepted. … Continue reading DevOps for Data Science – Defining DevOps
Data Scientists have often worked in a bit of a “silo” – meaning they were off to the side in an organization, maybe not even part of the Information Technology (IT) function. But that is changing. As data science projects are adopted into the mainstream, there is a need for structure. I’ve explained a modern … Continue reading DevOps for Data Science – Who needs it?