Real-Time Intelligence, Eventstreams, KQL & Fabric Activator

Instructor: Alaa Hady · Language: English or Arabic · Suggested duration: 2 days · Level: Intermediate to Advanced (Level 200–300)

Objectives

• Design streaming and event-driven analytics pipelines using Fabric Real-Time Intelligence.
• Ingest high-velocity streaming data (IoT, Kafka, Event Hubs, CDC, Workspace/OneLake events) via Eventstreams.
• Store and query billions of time-series/log records in milliseconds using Eventhouses and KQL (Kusto Query Language).
• Configure Fabric Activator to trigger automated real-time alerts, Teams messages, and Power Automate remediation workflows.

Outline and contents

1. Batch vs. Micro-batch vs. Real-Time Streaming: identifying high-ROI real-time use cases
2. Navigating the Real-Time Hub: discovering organizational streams, Azure events, and OneLake/Workspace system events
3. Eventstreams architecture: connecting sources (Event Hubs, Kafka, MQTT, CDC streams), no-code stream processing (filtering, tumbling/hopping windows), and routing to multiple destinations
4. Eventhouse & KQL Database fundamentals: why columnar + full-text indexing beats traditional SQL for telemetry, logs, and time-series data
5. Mastering KQL (Kusto Query Language): where, summarize, bin(), render, time-series anomaly detection (series_decompose_anomalies), and KQL Querysets
6. Bridging Real-Time and Lakehouse: enabling OneLake availability on KQL tables for instant Direct Lake & Spark access
7. Building live Real-Time Dashboards with auto-refreshing tiles and parameters
8. Fabric Activator: defining event rules, state change triggers, threshold alerts, and invoking Power Automate / Teams actions automatically
9. Hands-on Lab: Ingesting simulated IoT/Order stream data via Eventstream into an Eventhouse, writing KQL anomaly queries, building a Real-Time Dashboard, and triggering a Teams alert via Activator

Target audience

Data engineers, operations analysts, IoT/telemetry engineers, solution architects, and technical BI developers.

Expected outcomes

Participants can build end-to-end streaming analytics solutions in Fabric that detect operational anomalies in seconds and trigger automated business actions without human intervention.