Scalable Probabilistic Record Linkage Keeps Organizations Relevant

When organizations can’t easily and accurately combine and analyze data from disparate sources, they don’t gain actionable insight for any intended outcomes. Data silos tend to evolve separately across departments, creating inaccuracies and stifling breakthroughs. Every merger and acquisition requires seamless database integration to provide an ROI for having merged in the first place.

Record linkage builds a comprehensive view of all relevant information pertaining to the same entity: person, organization, or event. Yet most record linkage solutions today don’t have the scalability to keep up with aggressively growing data. The traditional approach of developing rules to exactly match records between datasets is time-consuming, tedious, inefficient, and impractical as the quantity of records and data sources constantly grows.

Faster, Accurate Matches

Probabilistic record linkage doesn’t require exact value matching to accurately identify matches. Because this type of linkage takes into account typos, incomplete data, personally identifiable information (PII) mismatch, and lifestyle changes to PII such as marriage, it holds distinct advantages over traditional deterministic linkage. The numerous rules needed for deterministic linkage to attempt to handle these occurrences are, by definition, always being put into place from a position of trying to catch up but never quite making it. The fuzzy hashing technique used in probabilistic matching adjusts thresholds to optimize positive and negative uncertainties and quickly arrive at data that is matched, sorted, and ready for analysis.

When PII can’t be disclosed and needs to be obfuscated before sharing—such as in public sector departments needing to communicate with outside agencies—Resultant’s solution protects PII while still providing the information needed for researchers to draw conclusions and test theories, for organizations to see the efficacy of their programs and make adjustments, and for policymakers to see results. Where on-prem servers are used, hybrid structures can leverage that security with the flexibility and adaptiveness of the cloud.

Solution in Action

When we collaborated with Indiana’s Management Performance Hub (MPH), we implemented a hybrid on-prem/cloud structure for record linkage. With a fuzzy logic solution in place, MPH could map 120 million records down to 34.5 million unique individuals in less than ninety minutes, enabling the agency to grow and act on their insights exponentially and securely share that data to do great things in the state.

Scalable probabilistic record linkage methodology allows organizations with disparate data and varying subsets of PII to identify relationships. Resultant’s unique solutions give rapid results, freeing your organization to act on the insights revealed.

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