Articles and news

Learn how to protect personal data and comply with the GDPR. Discover the key differences between pseudonymization and anonymization, and how to implement them securely.

Data masking is a strategy used to protect sensitive data in a dataset by transforming them into different data that maintain the coherence and consistency of the original set

Discover what data governance is, why it matters, and how to build a scalable framework with the right tools. Ensure compliance, security, and data value.

Learn how to mask sensitive data in CSV and JSON files using Python scripts. Apply substitution, truncation, and randomization to protect PII and other sensitive fields in development workflows.

Learn how to mask sensitive data in MySQL without breaking referential integrity or slowing down your QA cycles. This guide covers techniques to ensure compliance and automate your workflow.

Anonymization is no longer just compliance. Discover how automated strategies reduce data breach risks, ensure regulatory compliance, and accelerate innovation in the healthcare sector.

Failing to comply with the NIS2 Directive can cost millions. Learn the main risks and how to protect sensitive data in non-production environments.

Accelerate your development cycles and ensure data security. Discover how an automated data provisioning strategy eliminates manual bottlenecks and guarantees regulatory compliance.

Learn how to build a test data management strategy that ensures secure, high-quality, and compliant data provisioning across environments—boosting speed, control, and traceability.

Compare the best test data management tools of 2025 to improve your CI/CD workflows. Discover features, pricing, and benefits of tools like Gigantics, Delphix, and Informatica for secure, automated test data delivery.