How does iDBQuery handle inconsistent labels like "USA" vs "United States"?
iDBQuery can recognise that inconsistent labels — "USA", "U.S.", "United States", or "NY" and "New York" — refer to the same thing, and you can lock the mapping in the semantic layer so they're grouped correctly every time. That stops a single real category from being split across several spellings in your results.
Inconsistent categorical values are one of the quiet killers of accurate analysis: the same country, status, or product entered five different ways fragments your totals. iDBQuery helps you tame that without a full data-cleaning project.
- Recognises variants. It can identify that different spellings, cases, and abbreviations map to one real value and group them together when it aggregates.
- Make it permanent. Record the canonical mapping in the semantic layer or business glossary — "treat these five values as United States" — and every future answer applies it consistently.
- Surfaces the mess. You can also ask iDBQuery to show the distinct values in a column, which quickly reveals the variants hiding in your data so you can decide how to consolidate.
This is closely related to broader data-quality work, and iDBQuery supports both: cleaning up on the fly for an immediate answer, and codifying rules so the fix sticks. Because every figure is cited back to source rows, you can confirm that "sales in the US" now includes all the variant spellings rather than just one — turning inconsistent, real-world data into a trustworthy total.
Updated 2026-06-22