I mean there has definitely been an explosion of "Ops" terms, and not all of them are justified. I think MLOps makes sense to emphasise the three pieces though. I know people want the "Ops" part of "DevOps" to mean "magic optimization for anything", but it goes back to "ops" as in infrastructure/servers etc. So if DevOps is software engineering + deploying and running software reliably, then it still leaves a big gap on the "data" side - both in terms of orchestrating source data, but also in handling large model files, and tracking things like model decay.