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I'm curious - as someone who hasn't been paying super close attention to the space, what does it mean to be a full data platform? Is it just having all the different flavors of DB you might need all from one vendor, or is there also tighter integration than if you cobbled it together from multiple vendors?

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Essentially, yes. Different DB’s, federated queries (aka delta sharing, zero copy), definition/semantic layer tools, data engineering/pipelines, model training and notebooks, governance, data lineage, row/column/whatever access control.

It’s basically a luxury minivan. It’s may not be the fastest or prettiest or cheapest, but it’s a safe way for a large family of “data and AI people” to traverse a large organisation.

More seriously, I like to call it an “analytics workbench” in a professional setting.

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