Many businesses have built real-time data feeds on Azure to capture events at scale and drive timely decisions, but those solutions often relied on a patchwork of resources to ingest and process data making the overall component architecture harder to govern. As the velocity and volume of event data continues to rise, teams want simpler, more unified patterns for near real-time analytics without sacrificing throughput, reliability, or cost control.

In this session, we’ll show how to evolve established Azure real-time feed patterns into Microsoft Fabric Real-Time. We’ll walk through reference architectures for high-throughput event workloads, highlight what changes (and what doesn’t) when you move to Fabric-native streaming, and demonstrate how to blend streaming and batch data for downstream reporting and operational decision-making using both SQL and KQL.

We’ll focus on the Fabric items you’ll use to deliver near real-time outcomes, covering Eventstreams to ingest, filter, enrich, and route data. Before handing off to Eventhouse to store and query event data at speed with KQL. Then finally exploring Real-Time dashboards to turn streaming information into shared, actionable views.

You’ll leave with a practical mapping from Azure real-time feeds to a Fabric unified designs so you can modernise confidently, reduce architectural sprawl, and standardise how real-time data is delivered across your platform.