Description
The course is designed to provide a comprehensive understanding of real-time big data processing using Kafka, Spark, and Cassandra. In today’s world, data is produced at an unprecedented rate, and the ability to process and analyze this data in real-time is critical for making informed decisions. This course focuses on the fundamental concepts and architecture of Kafka, Spark, and Cassandra, and how they work together to create a robust big data processing pipeline.
Students will learn how to set up Kafka clusters and work with Kafka producers and consumers. Students will also learn about Kafka Streams, a client library for building real-time streaming applications that process data directly within Kafka.
Throughout the course, students will gain hands-on experience through practical exercises and projects that simulate real-world scenarios. By the end of the course, students will have a understanding of how to use Kafka, Spark, and Cassandra to build real-time big data processing systems.
Course Objectives:
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Understand the fundamental concepts of real-time big data processing
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Learn the architecture setup of Kafka, Spark, and Cassandra
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Understand how Kafka, Spark, and Cassandra work together to create a real-time big data processing pipeline
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Gain hands-on experience with Kafka, Spark, and Cassandra through practical exercises and projects
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Learn how to build a real-time big data processing pipeline from scratch
This course is intended for software engineers, data engineers, and data analysts who have a basic understanding of programming concepts and are familiar with SQL.
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