What is the focus of label-based discovery in data management?

Label-based discovery in data management primarily concentrates on ensuring that data is categorized and managed in a way that supports regulatory compliance. By applying specific labels to data, organizations can track and identify data that falls under various regulatory requirements, such as those pertaining to privacy, data protection, and industry-specific regulations. This approach allows for a proactive management strategy where data can be easily retrieved and analyzed in the context of compliance obligations.

Organizations face increasing scrutiny regarding how they handle sensitive data, and label-based discovery aids in classifying data accordingly to ensure compliance with laws like GDPR or HIPAA. This method empowers data governance frameworks, ensuring the organization can demonstrate compliance and respond effectively to audits or data breaches.

While general data maintenance, the discovery of all data types, and enhancing user accessibility can be important aspects of data management, they do not specifically target the identification and categorization of data to meet regulatory standards, which is the core function of label-based discovery.