What is OLAP (online analytical processing)?
OLAP, or online analytical processing, is a way of organising data into multidimensional structures — often called cubes — so you can slice, dice and aggregate metrics fast across dimensions like time, region and product. iDBQuery gives you the same kind of multidimensional answers from plain-language questions, without pre-building a cube.
OLAP is the technology behind classic "slice and dice" analysis. Data is arranged so that measures (like revenue or units) can be aggregated and viewed across dimensions (like time, geography, product or customer segment). The traditional form is an OLAP cube — a pre-computed multidimensional structure that makes queries like "revenue by region by quarter" fast to answer. The catch is that someone has to design and build the cube in advance, deciding ahead of time which dimensions and measures matter.
iDBQuery delivers the analytical outcome OLAP was invented for, but through conversation instead of cube-building:
- Ask across dimensions in plain language — "revenue by region by quarter, comparing this year to last" — and iDBQuery writes and runs the SQL to answer it.
- No pre-built cube. You don't have to predefine the dimensions and measures; you can ask a new cross-cut whenever a question occurs to you.
- Across sources, not one cube. Because iDBQuery builds one live model over your databases, spreadsheets and files, the "dimensions" can span systems that were never modelled together.
- Cited, not opaque. Every aggregated figure traces back to the source rows behind it.
So where OLAP asks you to model the analysis before you can run it, iDBQuery lets you explore multidimensional questions on the fly — and generate charts, tables and live dashboards from them.
Updated 2026-06-22