Data Streaming with AWS MSK and Change Data Capture

Modern data platforms rely on real-time data flow to make instant business decisions. Understanding how to capture, transform, and stream database changes as they happen is a critical skill for modern data engineers. This course provides a clear, conceptual path to mastering real-time data streaming and change data capture on AWS. You will transition from understanding basic streaming concepts to designing reliable, real-time ingestion pipelines. By exploring both Kafka-based architectures and cloud-native database streams, you will gain the knowledge required to select and implement the right streaming patterns for relational and NoSQL databases. What you'll learn: - Understand the core concepts of event streaming, change data capture, and real-time ingestion - Configure and manage Amazon MSK as a fully managed Apache Kafka service - Implement change data capture for relational databases using AWS Database Migration Service - Stream real-time updates from NoSQL databases using DynamoDB Streams - Apply real-time ETL transformations on streaming data using AWS Glue Streaming - Optimize data storage patterns for streaming outputs in Amazon S3 This course begins with essential streaming terminology, foundational architectures, and a comparison of Kafka-based versus native cloud streaming. You will then progress through structured written guides that explain how to configure change data capture, transform streaming data on the fly, and store it efficiently for downstream analysis. This course is designed for beginner data engineers, database administrators, and cloud enthusiasts who want to learn real-time data integration on AWS. No prior experience with Kafka or streaming technologies is required. Start reading to build your first real-time data streaming pipeline today.