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Data Governance for ML Platforms
When it comes to ML platform, is there any specific part of data governance framework that is most important for platform engineers? That's a good question. Usually when you look at MLOps tooling, the first touch point you typically have with consuming data from a data warehouse data lake host are artifacts. Some tools really focus on logging, storing meter data around your query. Other tools go even beyond that and they say, well, basically you locked the entire artifact and with artifacts. I mean, the data you actually use.