ANONYMIZATION Anonymization, pseudonymization and data masking - what are the differences?

In this era of digital transformation, we are processing more and more personal data. Companies, organizations and institutions manage a huge amount of information on a daily basis, which must be properly protected. This is why terms such as anonymization, pseudonymization and data masking are becoming so important. Although these terms are often used interchangeably, they have fundamental differences and applications. In this article, we explain how they differ, when they should be used, and how tools like Redact can help you effectively protect your data.

Anonymization is the process of transforming personal data in such a way that the data subject cannot be identified, either directly or indirectly. After successful anonymization, the data ceases to be personal data within the meaning of the RODO (Regulation of the European Parliament and of the Council (EU) 2016/679), which means that the rules for their protection no longer apply.

Example: instead of the patient’s data containing name, surname, PESEL and address – only anonymized information remains, e.g. about the course of treatment without the possibility of linking it to a specific person.

Advantages of anonymization:

• Data is not subject to RODO
• No risk of privacy violation
• Possibility of further data processing, e.g. for statistical analysis or research

Pseudonymization involves separating identifying information from the rest of personal data and replacing it with, for example, an identifier, code or alias. Although such data is protected and more difficult to attribute to a specific person, it is still considered personal data if it is possible to reconnect it to a specific identity.

Example: the PESEL number is replaced by a unique ID, but somewhere a key is stored to identify the person.

Advantages of pseudonymization:

• Reduces risk of data breach
• Useful for testing, analysis, reporting
• Meets RODO data minimization requirements.

Data masking is a technique for replacing real data with fictitious data, preserving the structure and format of the output. It is particularly useful in testing or training environments, where real personal data should not be used.

Example: the email address “jan.kowalski@firma.pl” is replaced with “test.user123@demo.com”.

Advantages of masking:

• Protects data while maintaining systems functionality
• Fast deployment and flexibility
• Secure testing of applications and systems

When to use which approach?

• Anonymization: when data is not needed in an identifiable form – such as for statistical analysis.
• Pseudonymization: when some form of identification is needed, but we want to minimize the risk.
• Data masking: in testing and training, where real data must not be used.

Tools such as Redact address the real data protection needs of organizations. Redact enables automatic processing of personal data and effective anonymization, as required by the RODO. What sets Redact apart?

• Automation – saves time and minimizes the risk of human error;
• Compliance – supports RODO, HIPAA, ISO/IEC 27001 compliant activities;
• Flexibility – ability to customize rules to meet the needs of a specific project;
• Scalability – works well for both small businesses and large corporations;
• Support for multiple data formats – the tool supports 25 document formats (PDF, DOCX, TXT, JPG and others).

The difference between anonymization, pseudonymization and data masking is crucial from an information security and compliance perspective. Choosing the right approach depends on the purpose of the data processing. In contrast, tools such as Redact provide effective, fast and compliant solutions that help companies protect data and avoid severe penalties. In a world where privacy is becoming the currency of trust, it makes sense to invest in proven technologies.