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Enable Real-Time Decision Making with Microsoft Fabric

🔴 Enable Real-Time Decision Making with Microsoft Fabric (Stream, Analyze & Act on Live Data with Fabric’s End-to-End Real-Time Stack) 📅 February 19 · 9 PM IST – Set Reminder ▶️ Modern organizations cannot wait for batch reports—decisions must be made as events happen. Microsoft Fabric’s Real-Time Analytics stack enables teams to ingest streaming data, query it instantly, visualize it live, and trigger automated actions based on real-time conditions. This session provides a hands-on, architecture-focused tour of Fabric’s real-time capabilities, helping participants understand how Eventhouse, KQL Queryset, Eventstream, dashboards, and Activator come together to power instant insights. Led by Ranjith Kumar, Corporate Trainer, this session is perfect for data engineers, analysts, architects, and organizations looking to implement event-driven intelligence. 🔍 What you’ll learn: 1. Eventhouse – The Centralized Hub for Streaming Analytics Understand how Eventhouse serves as the foundation for real-time workloads. Store, manage, and analyze massive volumes of streaming data efficiently. Organize data into real-time databases for high-performance querying. Use cases: operational monitoring, fraud detection, IoT analytics, digital experience tracking. 2. KQL Queryset – Real-Time Query Design & Optimization Write powerful Kusto Query Language (KQL) queries for instant insights. Optimize queries for speed, cost, and analytical depth. Design reusable query sets to support dashboards, investigations, and alerts. How KQL enables sub-second exploration of event streams. 3. Real-Time Dashboards – Monitor Live Data Instantly Build dashboards that update the moment new data arrives. Connect to Eventhouse or KQL queries for continuous visualization. Use charts, time-series views, and anomaly indicators for fast decision-making. Examples of dashboards used for SOC monitoring, logistics, operations, and manufacturing. 4. Eventstream – Ingestion, Routing & Transformation Ingest event data from IoT devices, apps, databases, APIs, or external sources. Route data to multiple Fabric destinations including Eventhouse, Lakehouse, and Warehouse. Transform data on the fly—filtering, mapping, enrichment, and standardization. Build scalable, fault-tolerant streaming architectures without complex code. 5. Activator – Automate Actions Based on Real-Time Triggers Configure triggers based on thresholds, anomalies, or specific events. Trigger workflows in Logic Apps, Power Automate, or custom applications. Examples: fraud alerts, SLA violation notifications, inventory reorder triggers. How Activator enables event-driven automation across the organization. 6. End-to-End Real-Time Scenario Live-stream → Eventstream → Eventhouse → KQL → Dashboard → Activator. A full walkthrough showing how all components integrate seamlessly for real-time action. 7. Live Q&A and Applied Guidance Ask questions on architecture design, ingestion strategies, KQL performance, automation, or Fabric adoption. 🎯 Who should attend? Data engineers & analytics professionals BI developers & dashboard designers Cloud architects building streaming platforms Operations, IoT, security, and monitoring teams Anyone implementing Fabric for real-time intelligence Speaker: Ranjith Kumar Corporate Trainer | Koenig Solutions Pvt. Ltd. 📢 Follow & Learn More: 🔗 Koenig Solutions: https://www.koenig-solutions.com 🔗 LinkedIn:   / koenig-solutions   🔗 Facebook:   / koenigsolutions   🔗 Instagram:   / koenigsolutions   🔗 Twitter (X): https://x.com/KoenigSolutions 🔗 Upcoming Webinars: https://www.koenig-solutions.com/upco... 🧠 If you want your organization to operate with real-time intelligence—detecting issues, responding instantly, and automating decisions—this session will show you how Microsoft Fabric makes it possible. 👍 Like | 💬 Comment | 🔔 Subscribe for more expert-led Fabric and real-time analytics sessions. #KoenigWebinars #KoenigSolutions #StepForward #MicrosoftFabric #RealTimeAnalytics #Eventhouse #Eventstream #KQL #DataActivator #StreamingData