Which technique involves gathering data and generalizing it to protect individuals' identities?

• A. Data Scrubbing
• B. Unencrypted Data (Cleartext/Plaintext)
• C. Aggregation and Banding
• D. Data Loss Prevention (DLP)

Answer: (C)

Aggregation and banding uses grouping to blur specifics and protect identities. By collecting data and then generalizing it—placing values into broader categories like age ranges or regional clusters—you keep useful trends intact while making it harder to pinpoint individuals. This is a classic data anonymization technique: you retain the ability to analyze patterns and drive decisions without exposing personal details.

Data scrubbing focuses on cleaning data and sometimes masking fields for quality purposes, but its primary goal isn’t generalizing values to hide identities. Data Loss Prevention tools aim to stop sensitive information from leaving an organization, not to transform data for privacy. Unencrypted data isn’t protecting identities at all; it remains vulnerable and provides direct access to raw information.