Sahil Walia

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 how to successfully move data engineering workloads to Snowflake. We will share best practices and review reference architectures that can ensure success while migrating to Snowflake. Topics include: - Migrating PySpark code - Migrating Notebooks to stored procedures - Data movement: Iceberg tables/Snowflake native tables - Code testing, CI/CD approaches, performance and optimization considerations - Data validation considerations and anti-patterns/considerations