ANONYMIZATION Anonymization without secrets - 5 data protection principles you need to know

In today’s digital world, data is as valuable as gold – and protecting it properly is the responsibility of every modern company. In the era of RODO and rapidly changing regulations, organizations must not only be aware of the risks, but also be proactive in minimizing the risks associated with personal data processing. One of the key protection mechanisms is anonymization – the process of permanently removing personally identifiable data.

In this article, you will learn 5 key data protection principles that will help you understand when and why to use anonymization.

Anonymization can be useful or required in many daily processes, especially when:

• you need to share personal data with external parties (e.g. law firms, auditors, government agencies),
• you process data for analytical purposes, but do not need information about the identity of individuals,
• you are preparing documentation for legal proceedings or internal audits,
• you want to limit the scope of personal data that leaves your organization (in accordance with the principle of minimization),
• you are archiving documents that originally contained sensitive data.

Here are the top 5 principles to consider implementing.

Rule 1: Minimize data

Don’t cluster more than you need – this is the basic premise of data minimization. It also means that personal data should not be passed on if it is not necessary for the purpose.

In practice:

• Instead of sharing full employee records, simply provide an anonymized version containing only the necessary information.
• In business analysis, it’s a good idea to remove identifying customer data if it’s not needed for statistics.

Rule 2: Limit storage

Pursuant to Article 5(1)(e) of the RODO, personal data may be kept only for the period that is necessary for the purposes for which they are processed. After its expiration – the data should be deleted or anonymized if there is a need for further use.

In practice:

• Anonymization makes it possible to prolong the usefulness of data without violating privacy laws.
• The anonymized data may continue to be stored for archival or statistical purposes.

Rule 3: Security of processing

The data controller is obliged to provide appropriate technical and organizational measures to protect personal data from unauthorized access, alteration or loss. Anonymization, as an irreversible process, minimizes the risk of data leakage.

In practice:

• Many organizations are not fully aware of exactly where personal data is stored and processed.
• Not all companies have security certifications, such as ISO 27001, which enforce control over access to information or documentation of data flows.
• Anonymization reduces the impact of a potential data breach because the data is no longer “personal.”

Rule 4: Accountability

The controller must be able to demonstrate that it has applied appropriate data protection measures – including anonymization, if the situation required it. The process should be documented and repeatable.

In practice:

• Anonymization processes should be repeatable and verifiable – manual “masking” of data may be insufficient and difficult to document
• The ability to work on different types of documents, the uniformity of anonymization rules applied, and the automation of the process facilitate the implementation of standards that can then be described and documented internally – for example, in information security policies or compliance procedures.

Rule 5: Pseudonymization is not the same as anonymization

Many companies mistakenly assume that pseudonymization (e.g., replacing names with initials) is enough. Meanwhile, only full anonymization makes the data no longer personal – and no longer subject to RODO. We write about the key differences in more detail in the article: “Anonymization, pseudonymization and data masking – what are the differences?”.

In practice:

• Changing names to initials or giving random identifiers is pseudonymization – it is still possible to establish identity.
• Removing or blurring all identifiable data (including indirect data like PESEL, TIN, etc.) is anonymization.

Data anonymization is not just an obligation – it is the foundation of responsible information management. Due to the scale and complexity of data, manual anonymization is often inefficient and fraught with the risk of errors. However, there are tools available on the market that support this process – one of them is Redact. This solution can automatically recognize and anonymize personal data in documents, regardless of their format. Redact can be helpful where time, accuracy and compliance are important. It won’t replace legal awareness or data protection policies – but it significantly supports their practical implementation.

Examples of using anonymization tools

• Due diligence and M&A transactions – Redact allows you to instantly prepare documentation for review by investors, without revealing personal information about employees or contractors.
• Litigation and audit proceedings – you can share documents with lawyers or auditors without risking a breach.
• Public publications and reports – prepare versions of documents that can be shared publicly without personally identifying information.