The technology, or technique, used to enable this functionality is known as data masking. Data Masking is a data security technique in which a dataset is copied but with sensitive data obfuscated. The replica is then used instead of the authentic data for testing or training purposes. Data masking does not just replace sensitive data with blanks. It creates characteristically intact, but inauthentic, replicas of personally identifiable data or other highly sensitive data in order to uphold the complexity and unique characteristics of data. In this way, tests performed on properly masked data will yield the same results as they would on the authentic dataset.
Data masking protects unauthorized access to and disclosure of sensitive, private, and confidential information so you can safely use de-identified data in development, testing, data warehouses, and analytical data stores. The most common example is in development of new or updated applications or in retro-fitting security controls to existing environments. Developers may not be allowed to see detailed personal information but at the same time they may need that data, or its equivalent, in order to test the application they are developing.