From Free-Text Chaos to Controlled Cleanup
Explain how AI-assisted cleanup should move messy free-text values into controlled, reviewable categories.
Daria asks Gemini to clean a campaign tracker. What changed from cosmetic cleanup to durable data quality? Before: categories drift every week. After: values are standardized and controlled. Historical variants collapsed into approved categories, so pivots and AI summaries count one real channel instead of several spelling accidents. A dropdown control was added for future rows, because cleanup should prevent the next inconsistency instead of only repairing the old ones. Ambiguous rows moved into a review queue, because AI should not guess when a category affects spend reporting. The range was formatted as a table after the values were fixed,…
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