Building Reporting Structures on S3 using Starburst Galaxy and Apache Iceberg

Starburst Galaxy, in conjunction with Apache Iceberg and AWS services like S3 and Glue, offers a streamlined approach for managing a data lakehouse architecture that eliminates the need for costly data migrations by keeping data stored on S3 while enabling efficient querying and reporting. By landing raw data in formats such as JSON on S3, users can leverage Starburst's Great Lakes connector to create structured and reporting tables with improved query performance through formats like Apache Iceberg and Delta Lake. This architecture supports both SQL BI reporting and ad hoc querying, allowing companies to build their data infrastructure with flexibility in processing engines and storage options, while maintaining performance gains and ease of data management. The tutorial also highlights the use of Trino, an open-source SQL query engine managed by Starburst Galaxy, to facilitate the easy handling of data and analytics on cloud storage platforms like S3, Azure ADLS, and GCP, making it a versatile solution for modern data challenges.