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Data Security in Apache Iceberg: An Enterprise-Ready Framework for Granular Protection
Abstract
In today’s data-driven world, sensitive information flows across diverse environments—cloud, on-premises, and hybrid architectures. Traditional perimeter-based security is no longer sufficient. This session introduces Protegrity’s vision for data-centric security within the Apache Iceberg ecosystem, ensuring that protection travels with the data itself.
Key Themes
- Security Beyond Location
- Data protection should not depend on where data resides. Whether in Snowflake, Parquet, or Iceberg tables, sensitive data must remain secure throughout its lifecycle.
- Embedded Protection
- Encryption at the data item level (e.g., each credit card number encrypted individually).
- Policies and permissions enforced at the role level—only explicitly authorized roles can decrypt.
- Encryption at the data item level (e.g., each credit card number encrypted individually).
- Enable AI-Driven Analytics Securely
- Demonstrate how encrypted data can still be leveraged for analytics and machine learning without compromising privacy.
- Showcase planned deployment using text-to-analytics workflows.
- Demonstrate how encrypted data can still be leveraged for analytics and machine learning without compromising privacy.
- Integration with Apache Iceberg
- Discuss how Protegrity’s approach complements Iceberg’s architecture for secure, scalable, flexible data storage.
- Highlight interoperability with Parquet Modular Encryption (PME) and future enhancements.
- Discuss how Protegrity’s approach complements Iceberg’s architecture for secure, scalable, flexible data storage.
What You’ll Learn
- Why Iceberg needs enterprise-grade, granular security—and what “pervasive protection” means in distributed data environments.
- A reference architecture for protecting Parquet-backed Iceberg tables using PME + external policy enforcement.
- Performance and operational benefits of chunk-level protection (including bulk processing and reduced overhead).
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