Implementing Zero Trust Security in Modern Enterprise Data Architectures​

As enterprise data ecosystems expand across hybrid and multi-cloud environments, traditional perimeter-based security models are no longer sufficient to protect sensitive information. Organizations are increasingly adopting Zero Trust Architecture (ZTA) to secure complex data environments where information flows across distributed platforms, services, and organizational boundaries.

This session explores how Zero Trust principles can be applied to modern enterprise data architectures, with a focus on the security implications of federated and centralized data models. The discussion examines how these architectures approach identity management, access control, and data governance within a Zero Trust framework. Federated architectures offer advantages in data sovereignty, localized policy enforcement, and distributed resilience, while centralized architectures enable unified security policies, centralized monitoring, and coordinated threat response.

The session will also highlight how AI-driven security capabilities are transforming Zero Trust implementations by enabling real-time threat detection, behavioral analytics, and automated response mechanisms. Additionally, the talk will address strategies for protecting AI-powered data pipelines, maintaining data lineage visibility, and ensuring compliance with evolving regulatory requirements.

Attendees will gain practical insights into designing secure, scalable enterprise data systems, understanding the trade-offs between federated and centralized models, and implementing Zero Trust strategies that strengthen data protection in AI-enabled environments.