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Data Minimization

Data Minimization is the principle that organizations should collect, use, retain, and disclose only the personal data reasonably necessary for specified purposes. This tag covers data minimization requirements across privacy and data protection laws, including the GDPR and U.S. state privacy laws, and their application to data collection, retention, sharing, AI systems, product design, privacy by design, and organizational data governance.

Data Protection by Design and by Default Under the GDPR: What Article 25 Requires

Data Protection by Design and by Default Under the GDPR: What Article 25 Requires

Learn what data protection by design and by default means under Article 25 GDPR, including privacy-protective defaults, data minimization, risk-based safeguards, accountability, DPIAs, processor selection, and how organizations can build data protection into systems from the start.

From Privacy by Design to Data Protection by Design: Principles and Practical Implementation

From Privacy by Design to Data Protection by Design: Principles and Practical Implementation

Privacy by Design embeds privacy into products, services, and business practices from the start. Explore its seven foundational principles, how they shaped Data Protection by Design under the GDPR, and practical steps organizations can take to turn privacy principles into everyday practice.

Österreichischer Rundfunk: When Salary Transparency Meets the Right to Privacy

Österreichischer Rundfunk: When Salary Transparency Meets the Right to Privacy

Austria required certain publicly controlled bodies to disclose the names and annual income of highly paid employees. The CJEU held that salary transparency may serve the public interest—but identifying individuals must still be necessary, appropriate, and proportionate.