Can I use iDBQuery to analyse a public open-data CSV?

Open-data portals (government statistics, census figures, price indices, geographic reference data) usually publish CSV files, which iDBQuery reads directly. There are two truthful ways to bring one in:

• Ingest the downloaded file. Download the CSV from the portal and ingest it; iDBQuery builds a live, queryable model from it in seconds.
• Connect via the API/URL. If the dataset is served at a stable URL or through an open-data API, iDBQuery's REST/API connector can fetch it and refresh on a schedule so it stays current.

Once loaded you can ask, in plain language, questions like the trend in a published index over time, or the top and bottom regions on a given measure, with every figure cited to the source rows. The most useful part is joining public data to your own: benchmark your sales against regional population or income, adjust internal figures by an inflation index, or map performance against public geographic data, all in one model without building a pipeline. iDBQuery does not force-copy the data into a separate warehouse; it queries what you load in place. Open-data CSVs can be large and occasionally messy, and iDBQuery's semantic layer and data-quality checks help it make sense of unfamiliar column names and spot issues, so a raw public dataset becomes something you can actually reason about alongside your business.