Henning Rauch
Microsoft, Principal Product Manager Kusto
Frankfurt am Main, Germany
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Henning Rauch is a Principal Product Manager at Microsoft and works on improving security, geospatial, and graph features for Eventhouse in the Fabric Real-Time Intelligence team. He came to Microsoft in 2016 and mainly worked with the automotive industry before moving to Microsoft’s R&D team. He studied computer science and has over two decades of experience in the industry.
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From Tables to Graphs in Minutes: Supercharging Kusto Graph Semantics with AI-Powered Development
GitHub Copilot and the Kusto MCP servers can help you move from manual table analysis to building persistent graph models in just a few minutes. Instead of spending hours writing queries and mapping relationships, you can use AI to analyze schemas, generate graph models, and create optimized queries for enterprise security analytics.
To follow along, you’ll need intermediate KQL skills, some experience with GitHub Copilot and data modeling, and familiarity with Azure Data Explorer or Eventhouse. During the demo, you’ll see real-time schema analysis, automatic graph model creation, and AI-generated queries using graph-match, graph-shortest-paths, and pattern analysis—all designed to improve performance for large-scale graph analytics.
This session was first publicly delivered in July 2025 at the WeAreDevelopers World Congress. It is designed for professionals with an interest in graph analytics, AI-assisted development, and enterprise-scale data modeling. There are no technical requirements to attend. The session is suitable for audiences familiar with KQL, GitHub Copilot, and Azure Data Explorer/Eventhouse.
Preferred Duration: 30 to 60 minutes.
Enhancing Cyber Security with KQL Graph Semantics and GQL
Uncovering hidden threats in cyber security demands more than a single tool or technique. It requires a truly integrated approach. This session demonstrates how to combine the strengths of KQL (Kusto Query Language), GQL (Graph Query Language), and advanced KQL graph semantics to unlock deeper insights.
You’ll learn how to design and query graph data structures, apply KQL graph operators to reveal complex relationships, and use GQL for advanced graph traversal and pattern matching. We’ll also showcase powerful graph visualization techniques that make it easier to interpret and communicate findings from interconnected datasets.
Through practical, real-world examples, you’ll see how this combined approach accelerates data exploration, exposes hidden dependencies, and enables advanced threat analytics. Whether you’re a cyber security professional, data scientist, or technology enthusiast, this session will equip you with the knowledge to elevate your security strategies and harness the full potential of your data.
Attendees should have a basic understanding of KQL and graph databases before joining the session. It is recommended to bring a laptop with access to Microsoft Fabric for hands-on participation. The session is designed for cyber security professionals, data scientists, analysts, and technology enthusiasts, and will run for 60 minutes including time for Q&A. All attendees will receive session materials, example datasets, and sample GQL queries for further exploration after the session.
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