Privacy is disappearing. From our morning coffee habits to our medical records, personal information flows freely between employers, businesses, government agencies, and social media platforms. Often without our knowledge or true consent. This isn't science fiction - it's our reality, and the databases are prime targets for breaches and abuse.

As Postgres administrators, we're on the front lines of this challenge. This talk introduces the PostgreSQL Anonymizer extension as a powerful solution for protecting sensitive data while maintaining its analytical value.

Through hands-on examples, we'll explore:

• Creating and implementing effective masking policies
• Applying dynamic masking for real-time data protection
• Generating anonymized dumps for development environments
• Producing privacy-preserving statistics

We'll conclude with cutting-edge developments, including:

• Implementing differential privacy
• Building a masking logical decoder
• Addressing privacy challenges in AI vector storage

Join us to learn practical techniques for enhancing data privacy in your PostgreSQL deployments.