data-classification

Automating data classification in Unity Catalog involves applying rule-based logic to schemas and sample content to detect PII, automatically reflecting sensitivity tags across catalogs, schemas, tables, and columns to enforce governance and compliance.

Schema-based data classification determines sensitivity by analyzing table and column names alongside data types. This rule-based approach automatically categorizes datasets without inspecting actual records, enabling immediate application of governance tags for policy enforcement.

Detecting and tagging PII across multiple catalogs uses content-based classification to optionally inspect sample data. This finer-grained analysis identifies regulated information and automatically applies appropriate PII tags to support access controls and compliance reporting.

Yes, you can enforce policy-driven data sensitivity levels in a multi-catalog environment. The classification workflow applies standardized tagging templates across the entire Unity Catalog hierarchy to maintain consistent governance and prevent policy drift.

The best way to apply governance tags for auditable workflows is through automated classification. Rule-based engines evaluate schemas and content, automatically attaching sensitivity tags at the column level to provide ready-to-integrate outputs for compliance reporting.

Yes, automated data classification works without manually inspecting every table by using schema-based classification. It analyzes names and data types to determine sensitivity, while content-based inspection remains an optional feature for detecting specific PII.