data-classification

To define data sensitivity levels for GDPR and CCPA compliance, establish clear categories like Public, Internal, Confidential, Restricted, and Top Secret. This classification framework ensures appropriate handling requirements and lifecycle management for organizational data assets.

The best way to create a data handling requirements matrix is to map each sensitivity level to specific access controls, encryption standards, sharing rules, and retention policies. This structured approach ensures data assets receive protection proportional to their classification.

To implement data lifecycle management procedures, establish structured processes for data creation, storage, usage, archiving, and destruction. This framework defines clear retention and disposal procedures to maintain compliance and secure data assets throughout their lifecycle.

Yes, you can use this data classification framework for a financial institution by defining customer PII as Restricted. This establishes requirements for encryption at rest and in transit, strict access controls, and specific retention policies like a 7-year retention mandate.

Data governance policy requires data discovery and inventory processes to accurately classify and manage organizational data assets. Implementing these procedures ensures comprehensive visibility and supports sensitivity labeling and lifecycle management across the entire data ecosystem.