Anonymization

Anonymization is removing personally identifiable information from data sets, so that the people whom the data describe remain anonymous.

Anonymization versus data deletion

• Anonymized data can still be used e.g. for statistical purposes. In the data object life cycle, anonymization often precedes complete data deletion.
• One data object usually has many relations to other data objects. The deletion of such object is often restricted by database delete rules. Anonymization represents a way around this limitation.

Examples of object types most likely to be anonymized: Person, Business Partner, User, Ticket...

Data anonymization in Valuemation entails:

1. Creation of an anonymization configuration
2. Running the anonymization process
   • manually
   • using the DPM (optional)