Do I need to build a pipeline or ETL before connecting a source?

One of iDBQuery's core promises is that you skip the data-engineering setup entirely. There is no pipeline to build and no ETL to maintain before you can ask a question.

• Connect, don't extract — you point iDBQuery at a source and it introspects the schema and builds a queryable model itself.
• No transformations upfront — you don't have to clean, reshape or stage data in advance; the semantic layer adds meaning, and you query the source as it is.
• No warehouse loads — sources are queried in place rather than copied into a central store on a nightly schedule.
• Minutes, not weeks — the gap between adding a source and getting your first cited answer is measured in minutes.

This matters because traditional analytics often stalls on the plumbing: building extraction jobs, modeling a warehouse, and keeping pipelines from breaking. iDBQuery removes that whole layer. When data does need refreshing — files or APIs — it's handled by simple scheduled syncs, not bespoke pipelines. The result is that a non-technical team member can connect a source and start asking questions the same day, while still getting answers cited back to the exact source rows.