AWS Data Store Optimization for Cost and Performance

Managing cloud data at scale can quickly lead to spiraling costs and sluggish queries if your storage layer is not properly optimized. This text-based course provides a clear, step-by-step path to configuring your cloud databases and storage systems for peak efficiency. You will learn how to balance performance requirements with budget constraints using proven architectural strategies. Starting with foundational database concepts and cloud storage terminology, you will quickly progress to practical optimization techniques. You will learn to reduce Redshift Spectrum costs, sync Glue partitions, export data to S3 in Parquet format, and manage DynamoDB expiration effectively. We also cover modern data engineering practices, including zero-trust security principles for access control and optimizing serverless data pipelines. What you will learn: Understand the core principles of cloud storage tiering and performance bottlenecks; Configure Glue partitions to keep metadata synchronized and query times low; Export relational data to S3 using the highly efficient Parquet format; Manage DynamoDB data lifecycles using Time to Live settings to reduce storage costs; Apply cost-saving strategies for Redshift Spectrum queries; Implement modern data access controls and security best practices. This course is designed as a structured, text-only learning experience where you can read explanations and analyze optimized configuration examples at your own pace. This course is perfect for beginners, junior data engineers, and cloud administrators looking to build a strong foundation in storage optimization. No advanced cloud architecture experience is required. Start optimizing your cloud data infrastructure today.