As analytics platforms increasingly support AI-driven and real-time workloads, data architects face a new challenge: how to manage transactional, analytical, and vector data together—without overcomplicating the architecture. This session dives into advanced design patterns using Oracle Autonomous Database 26ai as a multicloud data foundation alongside Microsoft Azure analytics services.

We’ll focus on architectural decisions rather than AI fundamentals, exploring how autonomous scaling, hybrid transactional/analytical processing, and native vector data support simplify modern data pipelines. Attendees will see when to use Oracle AI Database 26ai versus Azure-native analytics services, how data flows between platforms, and what trade-offs matter for performance, cost, and governance.

This session is designed for data engineers and architects who already understand cloud analytics concepts and want practical guidance for building scalable, AI-ready analytics architectures across clouds.