Data Ingestion on AWS: Building Reliable Pipelines

Every modern data-driven application relies on a solid foundation of clean, timely data. Understanding how to securely and efficiently move data from various sources into AWS is a critical skill for any aspiring data professional. This text-based course guides you through the core concepts of data ingestion on AWS. You will transition from understanding basic data transfer terminology to designing resilient, cost-effective ingestion workflows using both batch and real-time streaming approaches. What you'll learn: Understand the core differences between batch and streaming data ingestion patterns; Configure managed ingestion services including Database Migration Service (DMS) and AppFlow; Implement programmable ingestion workflows using Glue and Redshift COPY commands; Orchestrate complex data pipelines using EventBridge and Managed Workflows for Apache Airflow (MWAA); Process real-time streaming data with Kinesis and Managed Streaming for Apache Kafka (MSK); Apply modern data governance, schema evolution, and cost-optimization strategies to your pipelines. The course starts with fundamental concepts of data movement and storage, then progresses to step-by-step written explanations of managed, programmable, and streaming AWS solutions. You will reinforce your knowledge through comprehensive summaries and written conceptual quizzes at the end of each section. This course is designed for beginner data engineers, cloud practitioners, and developers looking to establish a strong foundation in AWS data pipelines, with no prior ingestion experience required. Start reading today to master the building blocks of AWS data engineering.