Which discipline entails differentiating data types (quantitative vs qualitative) and applying controls for confidential and PII?

Which discipline entails differentiating data types (quantitative vs qualitative) and applying controls for confidential and PII?

• A. Data Governance
• B. Metadata Management
• C. Data Quality
• D. Data Classification

Answer: (D)

Differentiating data types and applying controls for confidential information and PII is the work of data classification. This discipline involves labeling data according to its sensitivity and the protection it requires, so you know how it should be handled and who may access it. Recognizing data as quantitative (numbers, measurable values) or qualitative (descriptions, categories) helps determine the appropriate safeguards and controls for each item, ensuring that sensitive data is protected and privacy requirements are met. Once data is classified, you implement safeguards such as access restrictions, encryption, and handling rules tailored to confidential data and PII. Data governance provides overall policies and governance structures, but isn’t focused on the hands-on process of classifying data and assigning protection levels. Metadata management deals with information about data assets (like definitions and lineage) rather than the protection and handling rules themselves. Data quality concentrates on accuracy, completeness, and reliability, not on sensitivity labeling or access controls.

Differentiating data types and applying controls for confidential information and PII is the work of data classification. This discipline involves labeling data according to its sensitivity and the protection it requires, so you know how it should be handled and who may access it. Recognizing data as quantitative (numbers, measurable values) or qualitative (descriptions, categories) helps determine the appropriate safeguards and controls for each item, ensuring that sensitive data is protected and privacy requirements are met. Once data is classified, you implement safeguards such as access restrictions, encryption, and handling rules tailored to confidential data and PII.

Data governance provides overall policies and governance structures, but isn’t focused on the hands-on process of classifying data and assigning protection levels. Metadata management deals with information about data assets (like definitions and lineage) rather than the protection and handling rules themselves. Data quality concentrates on accuracy, completeness, and reliability, not on sensitivity labeling or access controls.