AWS Data Engineering Foundations: Build Modern Data Pipelines

Data is the backbone of modern decision-making, but transforming raw data into actionable insights requires a robust cloud infrastructure. This text-based course guides you through the core concepts of cloud-based data engineering using AWS tools. By reading through this comprehensive guide, you will transition from a beginner to a confident data practitioner capable of designing and maintaining reliable data pipelines. You will understand how to collect, store, catalog, and query data at scale using industry-standard cloud services. What you'll learn: Understand foundational cloud data concepts and the AWS global infrastructure; Configure secure storage solutions using Amazon S3 and implement data partitioning; Build automated data integration pipelines with AWS Glue and catalog your metadata; Query large datasets directly using Amazon Athena for serverless analytics; Implement modern data lakehouse patterns with AWS Lake Formation for secure access control; Orchestrate data workflows using modern cloud scheduling tools. The course begins with essential definitions and core data architecture concepts before guiding you through practical scenarios. You will progress from basic storage setup to query optimization and workflow automation through detailed written explanations and structured code snippets. This course is designed specifically for beginners, aspiring data engineers, and database administrators looking to transition to the cloud. No prior AWS or data engineering experience is required to start. Start building your cloud data engineering skills today with this structured written guide.