Data Classification

Data Classification is the process of categorizing data according to its sensitivity and protection needs into defined categories – the basis for applying protective measures in a targeted rather than blanket manner.

Three to four levels are common, such as public, internal, confidential and strictly confidential, supplemented by regulatory categories such as personal data. Classification is carried out manually by data owners, rule-based via patterns (such as credit card or personnel numbers) or, increasingly, automatically via machine learning; it becomes visible through labels that are permanently attached to the data. Consistency is decisive: a classification only takes effect when policies are linked to it – who may access what, what is encrypted, what may leave the organization and how long it is retained.

Data classification is thus the foundation on which Data Loss Prevention (DLP) and data security posture management build operationally – and a core component of Data Governance, which defines categories, responsibilities and rules across the organization.