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Are your batch pipelines too slow for today’s data demands? If you need to process data the second it's generated—whether it's user clicks, financial transactions, or IoT sensor readings—you need to understand event streaming. And in the world of real-time data, Apache Kafka is the undisputed king. 🚀 Support the Channel & Get Source Code: https://patreon.com/TheDataGuy?utm_me... ⚡ Get to The Next Level in Your Career: https://apps.apple.com/us/app/careerc... In this video, I break down the core concepts of Apache Kafka from scratch. We’ll move past the dense documentation and use simple, real-world analogies to explain how Kafka handles millions of messages per second without breaking a sweat. Whether you are a Data Engineer transitioning from batch to streaming, or a software developer building event-driven microservices, this is the foundational guide you need. In this video, you will learn: ✅ The Basics: What is Apache Kafka and why did LinkedIn create it? ✅ Core Components: A clear breakdown of Producers, Consumers, and Brokers. ✅ How Data is Organized: Understanding Topics, Partitions, and Offsets. ✅ Fault Tolerance: How Kafka replicates data so you never lose a message. ✅ Batch vs. Streaming: When to use Kafka (and when NOT to use it).