Natural-language Data Analysis

Natural-language analysis lets you describe a question about a dataset without writing every query yourself. The value comes from connecting that question to the correct fields, definitions, and calculations. Start with a small dataset and questions whose answers you already know. Ask to inspect the generated SQL, code, or spreadsheet formulas, and verify totals before relying on a visualization. This task is narrower than general data insights: it centers on your own uploaded or connected data and a reproducible calculation.

A practical workflow

1. Document the dataset, field meanings, date ranges, and business definitions.
2. Ask a precise question with the relevant filters and comparison period.
3. Inspect the generated query or calculation and confirm the expected row coverage.
4. Check the answer against a known total or independent calculation.
5. Save the query, chart, and assumptions so the analysis can be repeated.

What to compare

• Test missing values, duplicated rows, joins, and time zones.
• Check database permissions and how uploaded data is retained.
• Look for editable calculations and traceable chart inputs.
• Measure correct answers and review effort, rather than only response speed.

Choose tools for this workflow

Use the shortlist below to compare approaches. Test the same representative task in each product and inspect the output before expanding the workflow. Review the product profile for its scope and plan-specific limits.

Explore tools for this workflow.