Data Minimization Is the Obligation. Over-Retention Is the Symptom

In this whitepaper, you will learn about:

  • Learn why 30% of enterprise data is redundant, obsolete, or trivial (ROT) - increasing security, privacy, and AI risks while driving unnecessary storage costs
  • Discover why regulators are shifting from reviewing data retention policies to requiring continuous, operational enforcement of data minimization across the enterprise
  • Explore how automated discovery, classification, and policy-driven ROT remediation help reduce breach exposure, strengthen compliance, and build an AI-ready data foundation

DOWNLOAD WHITE PAPER


Every enterprise has data minimization obligations, but most struggle to operationalize them at scale. As hybrid environments expand and AI systems consume more enterprise data, over-retained information becomes more than a compliance issue—it becomes a growing security liability. In fact, 30% of 2025 breaches involved data sprawled across cloud, SaaS, and on-premises environments, with those incidents averaging $5.05 million per breach. Meanwhile, regulators are increasingly asking a simple question: Why did you still have that data?

This guide explores why traditional retention programs break down in modern enterprises and what it takes to continuously enforce data minimization across the entire data estate. Learn how organizations can identify redundant, obsolete, and trivial (ROT) data, automate remediation, reduce regulatory exposure, and create a trusted foundation for AI. With €5.65 billion in cumulative GDPR fines issued since 2018, and enforcement accelerating, operationalizing data minimization has become essential for both security and compliance.

Download the guide to learn how continuous data minimization helps reduce enterprise risk, strengthen compliance, and prepare your data estate for AI.

 

Data Minimization Is the Obligation. Over-Retention Is the Symptom

Award-winning technology, built by a proven team, backed by confidence. Learn more.


Frequently Asked Questions (FAQs)

Data minimization is the practice of retaining only the data that is necessary for business and regulatory purposes. It reduces security risk, lowers storage costs, supports compliance, and improves AI data quality.

ROT (redundant, obsolete, and trivial) data is outdated or unnecessary information that increases storage costs, expands the attack surface, and can negatively impact compliance and AI performance.

Regulators increasingly expect organizations to continuously enforce data retention policies, not just document them. Keeping unnecessary personal data can increase compliance risks and regulatory penalties.

Automated discovery, classification, and policy-driven remediation help identify and remove unnecessary data, reducing breach exposure, simplifying compliance, and ensuring retention policies are consistently enforced.

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