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Where DevOps and ML Meet - DevOps 156

Adventures in DevOps

CHAPTER

The Importance of Data Engineering in DevOps

Data as code doesn't really make sense. Who wants terabytes of data? I can't even imagine how that would be at your nomenclale and you're like, hey, I've got 18 petabytes of data that came in. Let's go through that manually. Like, no, not going to happen. So if you wanted to build this entire story right now of, hey, can I detect those changes. Can I filter effectively without having to manually go in and delete rows in a database that's terrible. You need monitoring and as Jillian said lineage. And that whole end to end product concept is data lineage"

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