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PURIST
30 days
Money-back window
14 h/wk
Modeled time saved
99.97%
Uptime SLA
< 7 days
Deploy time
PURIST AI
Claude Opus 4.7 · n8n v1.71 · <80ms
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Data
Intermediate

Record linkage

Identifying and connecting records that refer to the same real-world entity across different systems. Example: "J. Smith" in HubSpot, "Jane Smith" in Xero, and "Jane A. Smith" in Slack are the same person record linkage merges them into one unified profile.

Expert insight

Record linkage (identifying that two records from different systems represent the same real-world entity when they don't share a common ID) is inherently probabilistic, matching on name and email similarity will produce both false matches and missed matches, worth deciding an acceptable error tolerance rather than assuming linkage will be perfect.

In a real workflow

Customer records from the shop and the CRM are linked by email and name to form one customer view.

Common mistakes

  • Linking on weak matches only.
  • No way to undo wrong links.

Complexity level

Intermediate

Requires some familiarity with automation concepts.

Quick facts

Category Data
Level
Intermediate

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