Demo: Running the Stream Analytics Pipeline

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We run the Python race simulator and watch data flowing through the Event Hub in real-time. Then we start a Stream Analytics job that reads from the Event Hub, filters corrupted records, and outputs valid data to a data lake and Power BI.

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Previous Module Azure Synapse Link

This Module Stream Processing with Azure Stream Analytics

Introduction to Real-Time Data Processing

Azure Event Hubs

Demo: Event Hub Setup and Race Simulator

Demo: Running the Stream Analytics Pipeline

Stream Analytics Outputs and Windowing Basics

Advanced Windowing Functions

Real-Time Processing Architecture Summary

Next Module Stream Processing with Event Hubs and Databricks