Which method allows for the use of functional test data in new systems while protecting sensitive information?

Using data masking is an effective method for utilizing functional test data in new systems while ensuring that sensitive information remains protected. This technique involves altering the original data to create a version that retains its format and usability, but with sensitive elements obscured or replaced.

This is particularly useful in development and testing environments, where it’s essential to work with realistic datasets without exposing any confidential or proprietary information. For example, customer names, email addresses, and other personally identifiable information may be masked to prevent unauthorized access while still allowing developers and testers to validate system functionality.

In contrast, data encryption primarily secures data by converting it into a format that is unreadable without a decryption key, but it doesn’t allow the use of the data in its original form during testing. Data deduplication focuses on reducing the amount of storage by eliminating duplicate copies of data, which does not specifically address the need for data protection in testing scenarios. Lastly, data minimization refers to limiting the amount of data collected and processed, but does not provide a mechanism for safely using existing data in a functional context.