This session shows how organizations can move from raw machine and sensor data to faster, better operational decisions using SAS IoT analytics. It walks through the full lifecycle—data ingestion, exploration, model development, deployment, and decision support—and demonstrates how streaming analytics, guided modeling, containerized deployment, and agentic AI can help teams operationalize analytics at scale. The examples focus on practical industrial use cases such as predictive maintenance, manufacturing quality, worker safety, energy optimization, supply chain, and after-market service. The central message is that success comes not just from building models, but from turning data in motion into timely action.
Presenter: Bryan Saunders, SAS
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