identifiables

Identifiables are entities or data points that can be uniquely recognized within a given context. In information management and data modeling, an identifiable is any element that can be used to distinguish one item from another, either by itself or in combination with other data.

Identifiables may be individuals, objects, or events. In databases, they correspond to keys: natural keys such as a person’s name or a product serial number, and surrogate keys generated to guarantee uniqueness. In privacy contexts, identifiables include personal data and quasi-identifiers that could be combined to identify someone.

Common examples include a person’s national ID, email address, or biometric template; a product SKU or serial number; a device MAC address; a transaction ID; or a precise timestamp with location coordinates. Identifiables enable operations such as data linking, deduplication, access control, and audit trails, while also presenting privacy and security considerations.

Organizations address identifiables through governance measures designed to reduce risk. Data minimization, anonymization, pseudonymization, and strict access controls are typical strategies to mitigate re-identification and misuse. The concept also underpins database design and data integration, where identifying attributes support referential integrity and cross-system matching.

In practice, identifiability is context-dependent: an element may be identifiable in one dataset but not in another, depending on what other data is available. Understanding identifiables helps balance data utility with privacy, security, and governance requirements.