Stream Processing Frameworks Apache Flink and Apache Beam

This course will teach you how different frameworks work to provide stream processing and how to leverage them for the best outcome for your different real time use cases.
Modern businesses require real-time insights to stay competitive, but traditional batch processing creates dangerous delays in critical decision-making. In this course, Stream Processing Frameworks: Apache Flink and Apache Beam, you'll gain the ability to build robust, scalable real-time data processing systems that can handle a large number of events per second. First, you'll explore Apache Flink's distributed architecture and learn to implement low-latency stream processing for real-time ad pricing and click fraud detection in advertising platforms. Next, you'll discover Apache Beam's unified programming model that enables portable stream processing for ad analytics across multiple execution engines and cloud platforms. Finally, you'll learn how to compare and choose between Flink and Beam based on specific data requirements, performance characteristics and cloud deployment constraints. When you're finished with this course, you'll have the skills and knowledge of stream processing frameworks needed to architect and implement enterprise-grade real-time platforms.
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