Anonymization of production data to create functioning and useful test environment data

Abstract

This thesis will investigate different methods to anonymize production data to inject it or parts of it into the test environment. The different methods will be analyzed from different perspectives and some of them will be implemented in the implementation stage. Each method will be analyzed on a general plane but also from the point of view of a specific use case. The different methods might have to be used simultaneously for different parts of the process where different legal or technical requirements exist. Some methods (such as training an AI model) are more time-consuming to implement than others and, thus, they were not considered worth implementing in this thesis. We will also go through which methods work for our specific use case and which support our goals the most. Those will not be implemented but they will be considered in the comparison section of this thesis. Finally, this thesis will compare and summarize the analyses of the different methods in the summary section, and use cases will be suggested for the specific method for future use.