Streaming and Specialized Data Architectures with AWS

Modern businesses demand data in real time, yet traditional batch processing systems cannot keep up with the speed of live data streams. To build responsive applications, you must understand how to ingest, process, and store continuous flows of information efficiently. This course provides a clear, text-based path to mastering real-time data architectures using specialized AWS cloud services. You will transition from understanding basic data flow concepts to designing resilient, production-ready streaming pipelines. What you'll learn: - Understand the core principles of stream processing, event-driven architectures, and specialized data stores - Configure and manage real-time data streams using managed service alternatives on AWS - Process continuous data streams using Flink to perform real-time analytics and transformations - Store and query time-series data efficiently using Timestream for monitoring and metrics - Integrate third-party data feeds securely using AWS Data Exchange - Apply modern observability practices to monitor pipeline health, throughput, and system latency Starting with fundamental definitions and architectural patterns, this course guides you step-by-step through the mechanics of stream processing, specialized storage, and third-party data integration. You will learn to evaluate different data stores for specific workloads and design end-to-end pipelines that process data as it arrives. This course is designed for beginner cloud engineers, data analysts, and aspiring data architects who have a basic familiarity with cloud concepts but are new to streaming architectures. Start reading today to build the foundation for real-time data engineering.