Data Sensitivity Classification uses AI to automatically classify data assets by sensitivity tier (public, internal, confidential, restricted) enabling consistent access control enforcement, by scanning content and metadata for sensitive data patterns, across data governance and information security programmes.
Manual data classification leaves the majority of enterprise data assets unclassified, creating uncontrolled data exposure risk and impeding consistent access control enforcement, particularly for unstructured document repositories.
A classification model scans data asset content and metadata, identifies sensitivity indicators (personal data patterns, financial data elements, privileged information) and assigns a classification label applied as metadata to each asset, triggering downstream access control enforcement.
Increase in data asset classification coverage rate and reduction in sensitive data exposure incidents per year.
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