Data Minimization Under GDPR: Rules, Examples and Fines

In one line. Data minimization is the GDPR requirement that the personal data you collect be adequate, relevant and limited to what is necessary for the purpose you collect it for — Article 5(1)©. It is a field-level test, not a policy statement: every data point on every form has to be justified by a specific purpose, and “we might need it later” is not a purpose. The CJEU applied it literally in January 2025, ruling that a rail operator could not require customers to state whether they were Mr or Ms in order to sell them a ticket.

One of the fundamental principles enshrined in the General Data Protection Regulation (GDPR) is the principle of data minimization. This principle, outlined in Article 5(1)© (see the official texts on data minimisation and purpose limitation), mandates that personal data collected and processed by organizations must be adequate, relevant, and limited to what is necessary for the specific purposes for which it is processed. In this article, we will delve into the importance of data minimization, its practical implications, and how organizations can ensure compliance with this crucial aspect of the GDPR.

Data minimization in relation to the other principles

Data minimization is one of the seven data protection principles of Article 5, and it only makes sense in relation to two of them.

Principle	Article	Question it answers
Purpose limitation	5(1)(b)	Why are you processing this?
Data minimization	5(1)©	What may you collect for that purpose?
Storage limitation	5(1)(e)	How long may you keep it?

The order is not arbitrary. Purpose limitation is the input: until the purpose is defined precisely, the minimization test has nothing to measure against, which is why vague purposes (“to improve our services”) are the usual root cause of over-collection. Storage limitation is the output: data that was necessary at collection stops being necessary at some point, and minimization applied only at the point of collection leaves the rest of the lifecycle untouched. See the official EU texts on data minimisation and storage limitation for the exact wording of the interlock.

I - Understanding the Principle of Data Minimization

The principle of data minimization is a cornerstone of data protection and privacy. It aims to ensure that organizations collect and process only the personal data that is strictly necessary for the intended purposes. By adhering to this principle, organizations can reduce the risks associated with data breaches, unauthorized access, and misuse of personal information.

A - Key Elements of Data Minimization

The GDPR breaks down the principle of data minimization into three key elements:

1. Adequacy: The personal data collected must be sufficient and appropriate for the specified purposes. Organizations should carefully consider what data is truly necessary to achieve their goals and avoid collecting excessive or irrelevant information.

2. Relevance: The collected data must be directly related to the purposes for which it is processed. Organizations should ensure that there is a clear and justifiable link between the data they collect and the intended use of that data.

3. Necessity: The data collected should be limited to what is absolutely necessary for the specified purposes. Organizations should critically evaluate their data collection practices and eliminate any data fields or categories that are not essential.

B - Benefits of Data Minimization

Implementing the principle of data minimization offers several benefits to both organizations and individuals:

1. Enhanced Data Security: By collecting and storing only the necessary data, organizations reduce the potential impact of data breaches. If a breach occurs, the amount of compromised data is minimized, limiting the harm to individuals and the organization’s reputation.

2. Improved Data Quality: Focusing on collecting only relevant and necessary data helps ensure the accuracy and quality of the information. It reduces the likelihood of errors, inconsistencies, and outdated data, leading to more reliable and effective data processing.

3. Increased Trust and Transparency: Adhering to data minimization demonstrates an organization’s commitment to protecting individuals’ privacy rights. It fosters trust and transparency in the relationship between the organization and its customers or users.

C - Applying the test field by field

The principle becomes operational when you stop assessing “our data collection” and start assessing individual fields against a stated purpose. The question is always the same: could this purpose be achieved without this field? If yes, the field fails.

Field collected	Stated purpose	Verdict	Minimised alternative
Full date of birth	Verify the user is over 18	Fails	Boolean “over 18”, or year only
Title (Mr/Ms)	Sell a train ticket	Fails — CJEU C-394/23	Omit, or offer a free-text optional field
Home address	Deliver a digital product	Fails	Country only, if VAT rules require it
Phone number, mandatory	Contact about an order placed by email	Fails	Optional field, clearly marked
National ID number	Identify a customer in a CRM	Fails	Internal customer reference
Full CV retained after hiring decision	Recruit for one role	Fails at the retention stage	Delete, or ask consent to keep in a talent pool
CCTV covering a public pavement	Protect the shop entrance	Fails	Reframe the camera to the premises
Salary, in a leasing application	Assess ability to pay	Passes	—
IP address in security logs	Detect intrusion attempts	Passes	Shorten retention

Two patterns account for most failures. The first is the mandatory field that should be optional: making a phone number compulsory on a form whose purpose is served by email converts a nice-to-have into an unlawful collection. The second is the proxy field: collecting a precise identifier when a coarse one would do — a full birthdate instead of an age bracket, a home address instead of a country, an ID number instead of an internal reference. Both are usually inherited from a legacy schema rather than chosen, which is why the audit has to start from the database, not from the privacy policy.

Note that the test is applied against the purpose you stated, not the purpose you could have stated. This is where minimization and purpose limitation bite together: broadening the stated purpose to justify a field usually creates a transparency problem in the information notice instead of solving the minimization one.

II - Implementing Data Minimization in Practice

To effectively implement the principle of data minimization, organizations should take a proactive approach and embed it into their data collection and processing practices.

A - Data Mapping and Inventory

The first step in implementing data minimization is to conduct a thorough data mapping and inventory exercise. Organizations should identify all the personal data they collect, process, and store. This includes understanding the sources of the data, the purposes for which it is used, and the retention periods.

By creating a comprehensive data inventory, organizations can assess whether the collected data is adequate, relevant, and necessary for the specified purposes. They can identify any excessive or unnecessary data collection and take steps to eliminate or minimize it.

B - Privacy by Design and Default

The GDPR emphasizes the concept of privacy by design and default. This means that data protection should be integrated into the design and development of systems, processes, and products from the outset.

When designing data collection forms, applications, or systems, organizations should apply the principle of data minimization. They should carefully consider what data fields are essential and eliminate any unnecessary or optional fields. Default settings should be configured to collect the minimum amount of data required.

C - Regular Data Review and Deletion

Data minimization is an ongoing process that requires regular review and maintenance. Organizations should establish procedures to periodically review the personal data they hold and assess its continued relevance and necessity.

If certain data is no longer needed for the original purposes or has exceeded its retention period, it should be securely deleted or anonymized. This helps prevent the accumulation of unnecessary data and reduces the risks associated with data breaches or unauthorized access.

D - Staff Training and Awareness

Effective implementation of data minimization relies on the awareness and cooperation of all individuals within an organization. Organizations should provide regular training and guidance to their staff on the principles of data minimization and their responsibilities in upholding it.

Employees should be encouraged to critically evaluate data collection practices, question the necessity of certain data fields, and suggest improvements to minimize data collection. Creating a culture of data minimization within the organization is crucial for sustained compliance.

III - Challenges and Considerations

While the principle of data minimization is straightforward in concept, its practical implementation can present challenges for organizations.

A - Balancing Business Needs and Data Minimization

Organizations often face the challenge of balancing their legitimate business needs with the requirements of data minimization. In some cases, collecting additional data may be seen as beneficial for improving services, personalizing experiences, or generating insights.

However, organizations must carefully assess whether the potential benefits outweigh the risks and whether the additional data collection is truly necessary. In Mousse (C-394/23, 9 January 2025) the CJEU held that collecting a passenger’s title (Mr/Ms) was not necessary for the transport service and therefore breached data minimization — demonstrating that even seemingly innocuous data fields can trigger enforcement. They should explore alternative approaches that can achieve similar goals while minimizing the collection and processing of personal data.

B - Ensuring Data Quality and Accuracy

Data minimization should not compromise the quality and accuracy of the data collected. Organizations must strike a balance between collecting sufficient data to ensure the accuracy and completeness of their records while still adhering to the principle of minimization.

This may require implementing robust data validation and verification processes to ensure that the collected data is accurate, up to date, and free from errors or inconsistencies.

C - Addressing Legacy Systems and Data

Many organizations have legacy systems and databases that were designed and implemented before the GDPR came into effect. These systems may collect and store excessive or unnecessary personal data.

Addressing data minimization in legacy systems can be challenging, as it may require significant modifications or even the replacement of existing systems. Organizations should prioritize the review and remediation of legacy systems to ensure compliance with the principle of data minimization.

Recent Enforcement Developments

CJEU, Mousse (Case C-394/23, 9 January 2025)

The most consequential recent authority on data minimization. SNCF Connect required every customer buying a rail ticket to select “Monsieur” or “Madame”. The association Mousse complained to the CNIL, which closed the file; the Conseil d’État referred the question to the Court of Justice.

The Court held that the collection of a customer’s title is not necessary for the performance of a transport contract under Article 6(1)(b), and that where a controller relies on legitimate interest under Article 6(1)(f), the processing must still satisfy Article 5(1)© — personalising commercial communications by gender does not outweigh the rights of the data subject, particularly where customers who do not identify with either title are concerned. Adequate, relevant and limited, the Court confirmed, means limited to what is strictly necessary.

What makes this ruling operationally significant is not the amount at stake but the size of the field. A single dropdown with two values, present on essentially every European e-commerce checkout, was found unlawful. The reasoning generalises: if a field this small cannot survive the necessity test, neither can the larger ones that organisations collect out of habit — full birthdate, gender, marital status, mandatory phone.

CJEU, EDPS v SRB (Case C-413/23 P, 4 September 2025)

On 4 September 2025, the CJEU’s ruling in EDPS v SRB (Case C-413/23 P) reinforced the importance of assessing what data is truly necessary from the recipient’s perspective, confirming that pseudonymized data does not automatically constitute personal data for every holder. This has practical implications for data minimization: organizations sharing datasets can reduce compliance burden by stripping unnecessary identifiers before transfer. Additionally, the EDPB’s 2026 Coordinated Enforcement Framework action on transparency obligations (Articles 12-14 GDPR), launched on 14 October 2025 with DPAs across the EEA participating, will scrutinize whether organizations accurately disclose the categories and volume of data they collect – directly testing whether data minimization commitments stated in privacy notices match actual practice.

FAQ

What is data minimization?

Data minimization is the requirement in Article 5(1)© GDPR that personal data be adequate, relevant and limited to what is necessary for the purpose it is processed for. In practice it is a test applied to each field you collect: if the stated purpose can be achieved without that field, or with a less precise version of it, collecting it is unlawful. It applies at collection and throughout the lifecycle — data that stops being necessary must stop being held.

How do you demonstrate data minimization compliance?

Through the record of processing activities. Each activity should list the data categories collected against the purpose they serve, so that the necessity link is documented rather than asserted. Supervisory authorities test this by asking, field by field, why a data point appears in a form or a table. A DPIA is the other standard evidence: Article 35 requires an assessment of the necessity and proportionality of the processing, which is the minimization test written out.

What does the GDPR data minimisation principle require?

Article 5(1)© GDPR requires that only personal data that is adequate, relevant, and limited to what is necessary for the processing purpose is collected. Collecting extra data “just in case” is a direct violation.

How does data minimisation apply to forms and registration flows?

Every field in a form must be justified by a specific processing purpose. Optional fields must be genuinely optional. Collecting date of birth when only age verification is needed, for example, violates data minimisation.

What is the difference between data minimisation and storage limitation?

Data minimisation (Art. 5(1)©) controls what you collect. Storage limitation (Art. 5(1)(e)) controls how long you keep it. Both apply together — collect only what you need, then delete it when no longer needed.

What are common data minimisation violations and their penalties?

Common violations: collecting full birthdates when age is sufficient, mandatory phone fields for email-only services, CCTV footage retention beyond necessity. Fines can reach €20M or 4% of global annual turnover under Article 83(5). The UK ICO’s guidance on the data minimisation principle sets out the same expectation for UK GDPR.

Conclusion

The principle of data minimization is a fundamental aspect of the GDPR that aims to protect individuals’ privacy rights and reduce the risks associated with excessive data collection and processing. By collecting only adequate, relevant, and necessary personal data, organizations can enhance data security, improve data quality, and foster trust with their customers and users.

Implementing data minimization requires a proactive approach, including data mapping and inventory, privacy by design and default, regular data review and deletion, and staff training and awareness. While challenges may arise in balancing business needs and ensuring data quality, organizations must prioritize data minimization to achieve GDPR compliance and demonstrate their commitment to data protection.

By embracing the principle of data minimization, organizations can navigate the complexities of the GDPR, safeguard individuals’ privacy rights, and build a strong foundation for responsible and ethical data practices. For a complete overview of all GDPR requirements, consult our dedicated guide.