Aditya Challa

Operating an Iceberg lakehouse at scale means taming the operational overhead that grows with your data. In this chalk talk, we dive into table maintenance strategies—compaction, snapshot expiration, and orphan file cleanup—and discuss how Amazon S3 Tables automates these tasks.

Learn how to create end-to-end pipelines to power data and AI applications in Amazon SageMaker Unified Studio. We will cover how to implement both batch and streaming pipelines to integrate various data sources, optimizing data movement with modern ETL techniques.

Apache Iceberg is an open table format for very large analytic datasets. Apache Iceberg manages large collections of files as tables, and it supports modern analytical data lake operations such as record-level insert, update, delete, and time travel queries.