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4. Saving and Reusing Queries
Save a useful query, retrieve it from the Saved queries panel, and re-run it on refreshed data.
Every time you write a natural-language question in OUPI Data — for example, "total sales by region last quarter" — the AI translates it into a real query, runs it, and shows you the result along with the underlying logic. But what happens when you craft a query you know you'll need again next week, or next month on refreshed data? Instead of retyping it, you can save it. Saved queries live in a dedicated panel where you can retrieve, re-run, or use them as starting points for new variants. This turns one-off questions into reusable analytical assets.
To save a query, run it first from the Query screen. Once the result appears, look for the save option associated with that query. Give it a clear, descriptive name — something like "Monthly revenue by product line" rather than "Query 1" — so future-you (or a teammate) can identify it at a glance. The saved query stores the natural-language question and the logic the AI generated, so you always know what it does.
To retrieve a saved query, open the Saved queries panel. You'll see your list of previously saved questions. Select one to view its details, then re-run it. Because OUPI Data queries your live dataset each time, the results automatically reflect any data that has been refreshed or re-imported since the query was last executed. This makes saved queries ideal for recurring reports: import updated data, re-run the query, and get fresh answers instantly.
Use saved queries as building blocks: open a saved query, tweak the wording to ask a slightly different question, and save the variant under a new name. This lets you iterate quickly without starting from scratch each time.
Remember that each AI-powered query run consumes credits. The cost is shown before you execute, so you can decide whether to proceed. Saving and re-running a query costs credits each time it runs — saving itself simply bookmarks the question.
Go to the Query screen, type a question about one of your datasets (e.g., "average order value by month"), and run it. Then save the query. Navigate to the Saved queries panel and re-run it to confirm the result appears with current data.
You now know how to turn any natural-language question into a reusable saved query. The workflow is simple: run a query, save it with a clear name, then retrieve and re-run it from the Saved queries panel whenever your data is refreshed. Use saved queries as starting points for variants, and keep in mind that each execution consumes credits. This habit transforms ad-hoc questions into a reliable, repeatable analytics toolkit.