What is the difference between a measure and a dimension?
A measure is a numeric value you can aggregate, like revenue, quantity or duration, while a dimension is a descriptive attribute you slice and group by, like product, region or date. Measures are the numbers; dimensions are the categories you break those numbers down across.
Almost every analytical question combines the two: a measure summarised across one or more dimensions. 'Total revenue by region per month' uses revenue as the measure and region and month as dimensions.
- Measures are quantitative and additive (or semi-additive): sums, counts, averages. They live mostly in fact tables.
- Dimensions are qualitative context, the who, what, when, where, used in GROUP BY and filters. They live in dimension tables.
Getting this split right is the essence of a well-formed query; confusing them leads to nonsensical results (you cannot meaningfully average a category or group by a raw amount).
iDBQuery understands this distinction automatically. From a plain-language question it recognises which fields are measures to aggregate and which are dimensions to group or filter by, then writes the correct SQL. Its semantic layer classifies columns even when names are cryptic, and it can pull the measure from one source and a dimension from another, joining them for you. Every result is cited back to source rows, so you can confirm the number was aggregated across exactly the dimensions you intended.
Updated 2026-06-22