Shyamala Jayabalan

Stop the data silo and fragmentation tax. In this introductory hands-on lab, you will learn how to work on a single governed data copy that slashes costs and engineering effort. You will create Apache Iceberg tables in Snowflake Storage, apply Snowflake Horizon governance and secure multi-engine, and build Semantic Views to use AI to query your lakehouse with natural language. Achieve true data autonomy over your data and make your architecture AI-ready.

Join this session to learn about best practices and real-world examples for migrating data engineering and Spark workloads to Snowflake. We’ll cover legacy vs. Snowflake architecture and migration methods such as Iceberg and Delta direct, and we'll share pros and cons of integrating components such as Unity Catalog, Apache Iceberg™ tables and native Snowflake tables. Plus, we'll explore automated code conversion with the Snowpark Migration Accelerator, workflow orchestration with Snowflake Tasks and key data validation and observability techniques to ensure a smooth migration.