Data Engineering on Microsoft Azure - Azure for DE: 50 - Azure Stream Analytics overview

Hey Data Engineers! We've successfully ingested streaming data into Azure using Azure Event Hubs, but it's just sitting there, untapped and underutilized. It's time to unlock its potential and dive into the insights it holds! In the 50th episode of my free DP-203 course, I'll guide you through Azure Stream Analytics—a powerful tool for processing streaming data. We'll explore its windowing functions, which are essential for working with temporal data windows. Don’t miss out—let’s put that data to work and uncover what’s inside. Enjoy! ▬▬▬▬▬▬ IMPORTANT LINKS ▬▬▬▬▬▬ My LinkedIn profile: https://www.linkedin.com/in/piotr-tybulewicz-81a8793/ GitHub with my drawings: https://github.com/TybulOnAzure/DP-203 Stream Analytics documentation: https://learn.microsoft.com/en-us/azure/stream-analytics/stream-analytics-introduction Raspberry PI web simulator: https://azure-samples.github.io/raspberry-pi-web-simulator/ Real-Time Data Simulator: https://github.com/Azure-Player/Real-Time-Data-Simulator ▬▬▬▬▬▬ MEMBERSHIP ▬▬▬▬▬▬ Join this channel to get access to perks: https://www.youtube.com/channel/UCLnXq-Fr-6rAsCitq9nYiGg/join ▬▬▬▬▬▬ CHAPTERS ▬▬▬▬▬▬ 00:00 Introduction 00:52 Stream analytics overview 11:50 Creating a Stream Analytics Job 14:22 Components of the job 23:03 Creating the passthrough processing 47:21 Introduction to windows 49:59 Tumbling windows 1:02:25 Hopping window 1:17:40 Sliding window 1:28:06 Session window 1:33:34 Snapshots 1:35:36 Summary