Teradata is adding new privacy, security, and resiliency capabilities to its portfolio designed to address how sensitive data is protected, who and what can access it, and whether it remains available and recoverable when something goes wrong.
According to the company, Teradata addresses all three through an integrated approach that reduces raw identity exposure, enforces protection closer to the data, and keeps the intelligence powering AI available and recoverable.
In practice, that means protecting the intelligence behind AI without diminishing what makes it valuable, said Teradata.
Key capabilities and features include:
- Poly-Anonymization: reduces raw identity exposure while preserving the relationships and utility AI and analytics require
- Format-preserving encryption: protects sensitive values without changing their format or breaking downstream systems
- Post-quantum security and readiness: strengthens protection against emerging quantum-era threats through Anonomatic PII Vault and TLS 1.3 hybrid-key exchange for data in transit
- Immutable backup protection: prevents recovery points from being modified or deleted, strengthening cyber-recovery readiness
- Database-level high availability: an additional availability layer for mission-critical workloads, distinct from disaster recovery
“Privacy, security, and resiliency have historically been treated as separate problems with separate solutions. That approach doesn't hold up when AI is moving sensitive data across users, applications, models, and agents simultaneously. This announcement reflects how we think those capabilities need to work together, and it's the foundation for how we intend to extend that protection as AI environments grow more complex and the actors operating within them multiply,” said Sumeet Arora, chief product officer, Teradata.
Access control determines who can see sensitive data. Identity reduction changes how much identifying information needs to be present in the analytical environment in the first place. Teradata combines both, through an OEM partnership with Anonomatic, whose privacy capabilities are natively available to Teradata customers, said the vendor.
Poly-Anonymization replaces PII fields with a stable identifier while holding underlying identity separately within Anonomatic PII Vault, a post-quantum-secure environment built with multiple layers of overlapping security controls designed to protect sensitive identity information.
Authorized users can restore identity when a legitimate use case requires it, but everyone else works with data that retains its analytical structure, its relationships, and its utility. The result is an analytical environment where sensitive data can be used for AI, analytics, testing, and approved collaboration without broadly exposing who the data is about, said Teradata.
For data in transit, Teradata introduces post-quantum protection via TLS 1.3 hybrid-key exchange, which combines classical and post-quantum cryptographic algorithms in a single handshake. As quantum computing advances make current encryption standards increasingly vulnerable, organizations that establish cryptographic readiness now will be better positioned for what's ahead, the company said.
New native capabilities including dynamic data masking, data classification and tagging, column-level encryption, and global identity extend that protection across the data layer.
Through a partnership with Immuta, a data authorization platform between identity and enterprise data, dynamic ABAC brings identity-aware, attribute-driven access control that enforces policy consistently across users and AI workloads without duplicating data or rewriting governance rules, the company said.
Immutable backup protection strengthens cyber-recovery readiness by ensuring recovery points cannot be modified, encrypted, or deleted, even by privileged administrators. As ransomware increasingly targets backup data specifically, protected recovery points have become as critical as the protection strategies built around them. Teradata's resiliency architecture is designed to extend as cyber threats and recovery requirements evolve.
Additional capabilities including backup and recovery, scheduled data synchronization, and disaster recovery round out a more consistent Enterprise Data Protection experience, said the company.
Privacy capabilities, powered by Anonomatic and delivered by Teradata, are available now for Teradata Cloud on AWS, Azure, and Google Cloud.
Native data security capabilities including dynamic data masking, data classification and tagging, and column-level encryption are available on Teradata Cloud across AWS, Azure, and Google Cloud. Dynamic data masking, data classification and tagging are available for Teradata Factory and on-premises deployment options.
Teradata Enterprise Data Protection including immutable backup protection is available now on Teradata Cloud across AWS, Azure, and Google Cloud with availability on Teradata Customer Cloud planned in the coming months.
For more information about this news, visit www.teradata.com.