Assess whether a dataset is findable, accessible, interoperable, and reusable enough for a proposed AI data science workflow.
The question is not "Do we have data?" The question is whether the data can survive contact with an AI workflow. FAIR gives you four checks before the modeling rush begins. Findable asks whether the right source and owner can be located. Accessible asks whether the team can use the data through approved paths. Interoperable asks whether it can connect cleanly to other sources. Reusable asks whether definitions, provenance, and constraints are clear enough that another analyst would not have to guess. Findable If the team cannot point to the canonical source, you will train on whoever exported the latest…
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