Privacy-preserving Data Analysis

Privacy-preserving data analysis involves techniques that allow researchers or analysts to extract useful insights from data without exposing sensitive personal information. It ensures individual privacy by applying methods such as data anonymization, encryption, or differential privacy—adding controlled noise—to prevent identification of specific individuals. This approach balances the need for valuable data insights with the obligation to protect individual privacy, enabling organizations to analyze data responsibly while maintaining trust and complying with privacy regulations.