How does iDBQuery understand synonyms and business jargon for the same thing?
iDBQuery maps everyday synonyms — "clients", "accounts", "customers", or "revenue", "sales", "turnover" — onto the right tables and columns using its semantic layer and a business glossary you can edit. So different people can phrase the same question their own way and still get the same cited answer.
Teams rarely use the exact column names in a database. Finance says "turnover", sales says "bookings", and the table is called `net_rev`. iDBQuery bridges that gap so plain language works.
- Semantic layer. It captures the meaning behind cryptic tables and fields and links common terms to the underlying structures.
- Business glossary. You can define your own vocabulary — declare that "active customer" means a specific status, or that "GMV" maps to a particular measure — and iDBQuery honours it on every question.
- Auto-enrichment. On connect, a background step proposes meanings for obscure names, giving the model a head start before anyone edits anything.
The payoff is consistency: whether a new joiner asks about "clients" or a director asks about "accounts", they resolve to the same entity and return the same number. This matters most in cryptic or legacy schemas where field names give no hint of meaning. And because iDBQuery still shows its SQL and cites the source rows, you can see exactly which table a synonym resolved to and correct it once if the mapping is wrong.
Updated 2026-06-22