What is an Anonymization treatment?

An anonymization treatment identifies and replaces sensitive data in your database with realistic fake data. When you create a treatment, Test Data Manager automatically scans your database to detect personally identifiable information (PII) and assigns appropriate masking datasets to each column.

Treatments are reusable, once created, you can run them multiple times against databases with the same schema.

Quick Links

→ Creating an Anonymization Treatment
→ Reviewing and Editing Masking Rules
→ Running an Anonymization Treatment
→ Download for CLI Use
→ Troubleshooting

Related Topics

- Learn about Subsetting treatments
- Understand default datasets