How DataBuddy Uses Ontology and a Semantic Layer to Answer Enterprise AI Semantic Architecture Questions

DataBuddy proposes an enterprise AI semantic architecture approach that establishes the skeleton with ontology and provides the scale with semantics, addressing the problem that the same business question yields different answers due to differing definitions. Using "What was the DAU of customers in East China last month?" as an example, the article points out that DAU has three deduplication definitions—by account, by natural person, and by device—and that there is also disagreement over whether "last month" means the calendar month or the most recent 30 days. The semantic model is responsible for pinning "DAU" to a single, previewable, verifiable, and lineage-traceable calculation logic.