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Guide · Data & Decision Intelligence · 11 min read

One Reality, Many Records: Resolving Identity in Fragmented Data

How records from fragmented systems can be reconciled into reliable views of people, organisations, assets, and relationships.

An organisation may hold many records about the same real-world subject. Entity resolution determines which records refer to the same person, company, vehicle, device, or location while preserving uncertainty and evidence.

01

Define the entity and the use case

Resolution quality is contextual. Matching customers for service may tolerate different uncertainty than identifying counterparties for risk. Establish the entity types, required attributes, decision consequences, and acceptable false-match trade-off.

02

Combine deterministic and probabilistic evidence

Exact identifiers are useful but rarely sufficient. Strong systems standardise fields, compare names and addresses, account for missing values, weight evidence, and use relationships or behaviour without turning a weak similarity into certainty.

03

Make identity decisions explainable

Retain the records, comparisons, scores, rules, versions, and stewardship actions behind every resolved entity. Teams need to understand why records were joined, separated, or sent for review.

The Dynetiks perspective

Strong technology begins with the complete operating context. Connect the disciplines early, validate against real constraints, and design for the lifecycle—not merely the launch.