Treating data as a product means somebody is accountable for its consumers being satisfied, not merely for the pipeline running. That implies documentation, a stable interface, a declared refresh frequency, quality guarantees, a way to report a problem, and a plan for changing it without breaking downstream users. It is the same discipline a software team applies to an API, applied to a table.
In practice. A data product is only a product if it has named consumers. Two teams that depend on it, with an agreed refresh and a route to complain, is enough. Without consumers you have a dataset with extra paperwork.
Where it goes wrong. Every existing table gets relabeled a data product with no change in ownership, documentation or commitment. Renaming does not create accountability. The test is simple and unforgiving: if the load fails on a Sunday, does somebody who is not the platform team know, care, and have a stated obligation to respond?