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Core Use Case: Comprehensive Data Privacy Management: From Secure Test Data Generation to Dynamic Access Control in Production

Description: This session provides a deep dive into postgresql-anonymizer, showcasing its role as a powerful, production-ready solution for robust PII/PHI protection across the entire data lifecycle. Leveraging features from its 2.0 release—including flexible custom masking functions, significant performance gains, and enhanced security—we will explore practical strategies for implementing granular data masking and anonymization. The presentation will meticulously demonstrate how to:

Generate Secure, Realistic Test Data: Employ static anonymization techniques (faking, shuffling, partial masking) to create compliant, non-identifiable datasets for development, testing, and analytics, effectively mitigating the risk of sensitive data exposure outside of secure production systems.

Implement Dynamic, Role-Based Access Control: Utilize postgresql-anonymizer in conjunction with PostgreSQL's Row-Level Security (RLS) to enforce real-time, context-aware data masking directly on live production systems, ensuring that only authorized individuals see sensitive PII/PHI while others interact with masked representations.

Achieve and Maintain Regulatory Compliance: Address stringent privacy regulations such as GDPR, HIPAA, and CCPA by demonstrating effective data redaction, pseudonymization, and the facilitation of "right to be forgotten" principles through controlled irreversible anonymization.

Attendees will gain actionable insights into maintaining data utility for business operations while rigorously adhering to privacy mandates, enhancing their organization's overall data governance posture.