Christopher Schmidt
Principal Program Manager, Microsoft
Columbus, Ohio, United States
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Christopher Schmidt is a Principal Program Manager with deep expertise in real-time data systems, specializing in message streaming and event-driven architectures. At the forefront of Microsoft’s efforts in modern data platforms, Christopher has led initiatives that transform how organizations harness streaming data for intelligent, scalable decision-making. His work spans resilient, low-latency pipelines to AI-led consumption technologies.
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Diving into Event-Driven Architectures in Microsoft Fabric with Real Time Intelligence
Real-time intelligence is revolutionizing the way we process and analyze data, making operations faster and more efficient across various applications. In this session, we'll explore how Microsoft Fabric empowers you to harness event-driven architectures in a low code SaaS platform, transforming data in flight. We'll dive into the core concepts, practical applications, and best practices that make these architectural systems the most powerful data pipelines you've ever seen. Due to its powerful engine, we can even perform complex tasks like anomaly detection and predictive analytics directly on the streams of data as they are being processed!
You will learn:
-Grasp the basics of real-time data processing and event-driven architectures
-Understand how data transformations work in real-time messaging systems and how they differ from traditional data pipelines
-Various action systems that can be used to integrate data into the fabric of the business
Beyond the Star Schema: Augmenting Power BI with an Ontology and Real-Time Events in Fabric
Classical dimensional models and Power BI semantic models are excellent at reporting the past but struggle with real-time signals, causal reasoning, and shared business meaning across apps, AI, and BI. In this session we show how to augment your existing star schemas with three additive layers in Microsoft Fabric: Eventhouse for real-time events, a Lakehouse, and ontologies that encodes rules such as "at-risk shipment" and "delay cause". Ontology-derived outputs feed back into Power BI as familiar fact tables, and Copilot and Data Agents can turn them into natural-language explanations. Start seeing improvement to your existing data stack, without feeling as if you need to reinvent the wheel.
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