CRM rot: a dedupe review that never bulk-deletes | Faceless AI - Dataspheres AI

Duplicate records corrupt pipelines quietly: two rows for one customer, outreach split across both, reporting counting them twice. Practitioners in this th...

Duplicate records corrupt pipelines quietly: two rows for one customer, outreach split across both, reporting counting them twice. Practitioners in this thread on data cleanup agree on the failure mode — and on the fear: bulk "fix" operations that destroy good data along with the bad. Detect loudly, merge one pair at a time Dataspheres datasets now include a dedupe review: a read-only scan matches rows on normalized key columns (case, whitespace and punctuation insensitive) and surfaces candidate pairs. Nothing merges automatically. Each pair is an explicit keep/drop decision, and the kept row is enriched with any values the dropped row had that the kept one lacked. One action, one pair, reversible judgment applied by a human. Import hygiene that prevents round two Normalize on entry: trim, lowercase emails, strip formatting from phone numbers. Pick one natural key (usually email) and check it before insert, not after. Keep provenance: a source column tells you which import created the duplicate wave. Sources: the linked thread; the dedupe flow verified with seeded duplicates (scan found exactly the planted pairs; a merge removed exactly one row) 2026-08-05.