Next-Gen Digital Twins on Microsoft Fabric: Real-Time, AI-Driven, Cloud-Scale

Modern digital twins demand real-time context, elastic scale, and AI-ready data. This session shows how to build next-generation twins on Microsoft Fabric—from streaming ingestion to actionable intelligence—so your virtual models stay accurate and responsive as conditions change. We’ll design an end-to-end reference architecture that blends IoT telemetry, Eventstreams/Eventhouse, Lakehouse/OneLake, semantic models, and real-time analytics, and we’ll connect these to twin graphs (e.g., Azure Digital Twins) for stateful reasoning. You’ll see patterns for low-latency processing, AI/ML enrichment, and closed-loop automations, plus how to secure, govern, and cost-optimize at scale. Expect live samples that cover device-to-dashboard flows, anomaly detection for predictive maintenance, and event-driven actions that improve reliability and efficiency. If you’re ready to move beyond dashboards to continuously learning, operational twins, this talk gives you the templates, code, and operating practices to do it—fast.

1. Design a real-time digital twin architecture Learn how to build an end-to-end reference architecture using streaming ingestion, Eventstreams/Eventhouse, Lakehouse/OneLake, and semantic models, integrated with twin graphs (e.g., Azure Digital Twins). 2. Apply AI and analytics for operational intelligence Understand patterns for low-latency processing, anomaly detection, predictive maintenance, and AI/ML enrichment that turn raw telemetry into actionable insights. 3. Operate digital twins at cloud scale Discover best practices for security, governance, cost optimization, and closed-loop automations that enable reliable, scalable, and production-ready digital twin solutions.