Building and visualizing your data lakehouse with AWS, Trino, and Iceberg

Antony Prasad Thevaraj, Senior Partner Solutions Architect at AWS and Monica Miller, Senior Developer Advocate at Starburst led a workshop on building and visualizing your data lakehouse with AWS, Trino, and Iceberg.

The data lakehouse is a cost-effective, performant, and flexible data architecture that capitalizes on the separation of storage and compute. By choosing Amazon S3 as your storage, and Starburst as your compute engine, you are building a foundation for your end-to-end data platform that provides a single point of access for teams to discover, govern, analyze, and share data in and around your data lakehouse. In this session, Antony and Monica break down the components of a data lakehouse, exploring technologies such as Apache Iceberg and Trino, while also utilizing native cloud services such as Amazon S3 and Amazon Glue. After building a data lakehouse, the pair will demonstrate visualizing data within the lakehouse with AWS Quicksight breaking down barriers by showcasing how organizations can drive extremely efficient time to insight.