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2. I hate the name data lake but I’ve always used them as part of a pipeline. It’s useful to keep the raw data around when you need to recover / replay the pipeline.

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I think most data lakes really turn into a data swamp as people/orgs are not diligent enough to keep them in a good shape. In absence of costs, people never delete anything voluntarily and the garbage will grow monotonically until it takes up all space.

That applies to databases as much as data lakes.

I don't know why it's so hard to get across that data expires in the same way that language changes.

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