Deduplication

Definition

Definition Deduplication is the process of identifying and removing duplicate entries that refer to the same entity or person. It’s a core quality function in any investor dataset because duplicates distort coverage, inflate record counts, and create workflow errors. Context In family office datasets, duplicates happen for predictable reasons: name variations (e.g., “Smith Family Office” vs “Smith Office”), subsidiaries and holding entities treated as separate offices, and contacts appearing multiple times due to different emails or title variants. Deduplication is not only about deleting duplicates—it’s about retaining the best version of the record, preserving relationships, and ensuring key fields remain consistent after consolidation. Why It Matters Duplicates create false confidence. A user may believe they have broad coverage when they are repeatedly seeing the same office in different forms. In outreach workflows, duplicates lead to repeated messages across team members, damaging reputation and reducing response likelihood. Deduplication is one of the clearest signals that a dataset is operationally safe. Key Takeaways Duplicates inflate counts and damage usability Dedup must preserve relationships and best fields Outreach and coverage ownership depend on clean records Deduplication is a baseline requirement for trust