AWS S3 Tables with Apache Iceberg integration represents a significant advancement in data lake technology that can dramatically reduce costs for analytics solutions. The implementation of Iceberg in AWS S3 has demonstrated remarkable cost savings of up to 90% in some deployments, primarily by addressing small file problems, optimizing storage efficiency, reducing API request costs, and improving query performance. Key use cases that benefit most include high-volume data lakes suffering from small file proliferation, analytics solutions requiring frequent schema changes, systems with repetitive query patterns on common datasets, and applications needing advanced features like ACID compliance and time travel capabilities. Organizations can leverage these capabilities to not only reduce their direct storage costs but also decrease associated compute expenses, streamline data engineering workflows, and build more cost-effective modern data architectures. Understanding S3 Tables and Apache...