Data Privacy 101
There are various methods to protect data – here is an overview of the key differences:
Anonymization
Personal data is altered so that it can no longer be attributed to a specific individual. Fully anonymous – re-identification is impossible. The original data is permanently lost during this process.
Pseudonymization
Personal data is replaced by a pseudonym, such as a UUID or an ID number. Linking back to the individual is only possible with additional, separately stored information. The data remains usable for analysis but is significantly more secure.
Masking (Redaction)
Parts of the data are hidden or replaced, for example, a credit card number: 1234—XXXX—5678.
The visible information is intentionally restricted. Masking is particularly useful for
software testing, training, or reporting.
Data Synthesis (Synthetic Data)
New, artificial data is generated that statistically resembles the original data but does not represent real people. This method is ideal for training AI models and analytics without incurring data privacy risks.
Key Takeaways at a Glance:
- Anonymization = Data is "gone"
- Pseudonymization = Data is "hidden"
- Masking = Data is "covered"
- Synthesis = Data is "reinvented"