Big data demands big solutions—but traditional data lakes often fall short on performance, consistency, and scalability. Enter Apache Iceberg: an open-source table format designed to bring ACID transactions, schema evolution, and high-performance querying to modern cloud-native data architectures.

For Python developers and data engineers, Iceberg offers powerful capabilities for managing massive datasets efficiently. Whether you're ingesting, querying, or evolving data, Iceberg ensures transactional integrity, optimized performance, and seamless integration with various compute engines.

From time travel and partitioning strategies to best practices for scalable data lakes, this session will demystify Apache Iceberg and provide the insights you need to build future-ready, cloud-native data pipelines.