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Entity Resolution

Entity Resolution is the process of identifying, matching and merging records that refer to the same entity - such as a person of interest, organization or device - across multiple datasets.

Overview

In intelligence and investigative work, information about a single entity often exists across disconnected systems and formats. Entity Resolution unifies these fragments, creating a single, accurate view that helps analysts reveal hidden connections, reduce duplication and prevent false leads.

What Is Entity Resolution?

Entity Resolution uses algorithms and identifiers (names, addresses, phone numbers, IPs and other attributes within the datasets available) to determine when multiple records describe the same real-world entity. This ensures that investigations and intelligence processes rely on consistent and accurate data. Explore Cognyte’s Entity Resolution blog for examples in security and law enforcement.

How Does Entity Resolution Work?

The process involves data ingestion, cleansing and probabilistic or deterministic matching. Advanced systems apply graph analytics to link entities and detect relationships, even when identifiers differ. Cognyte’s decision intelligence platform uses these techniques to unify data provided by the customer from all its relevant sources, including government and commercial databases as well as intelligence and operational systems.

Why Use Entity Resolution & Why Is It Important?

Entity Resolution eliminates duplication, reduces analytical errors and enhances situational awareness. In law enforcement and national security, it enables faster case progression, improved collaboration and accurate attribution of people, organizations and assets.

Cognyte’s Solution for Entity Resolution

Cognyte’s decision intelligence platform incorporates powerful entity resolution tools to unify structured and unstructured data. The result is a clear, connected intelligence picture that accelerates investigations and improves analytical accuracy.