Not all data needs the same protection. A customer price list is handled differently from payroll data or an acquisition plan. Data classification makes this difference explicit and therefore manageable.
Levels
Four levels are common: public, internal, confidential and strictly confidential. More levels increase precision but also effort and error rates; fewer than three distinguish too little. Each level is described with examples so employees can apply it confidently day to day.
Rules per level
The level determines who has access, where data may be stored, whether it may be shared externally, whether it must be encrypted and how it is deleted. These rules link classification with the permission concept, the deletion concept and the technical and organisational measures.
Distinction from data protection
Data protection law distinguishes personal data and sensitive personal data. Classification is broader: it also covers trade secrets and internal information without personal reference. Sensitive personal data usually ends up in one of the highest levels.
Implementation
Classification that exists only on paper has no effect. Modern platforms allow sensitivity labels on documents and emails that enforce encryption and sharing rules automatically, plus data loss prevention rules. Before introducing AI assistants such as Microsoft 365 Copilot, classification is especially important because they find everything a user can access.