Kamesh Sampath

Stop pipeline sprawl and the cost of data duplication. In this advanced lab, you will learn to perform secure, in-place transformations across your entire data estate. You will connect externally managed Iceberg tables with Catalog Linked Databases to always work on fresh data without ETL, build efficient and declarative pipelines with Dynamic Tables for Iceberg preserving multi-engine access to your data, and implement business continuity to ensure your production data is always available.

Data and AI engineers are trapped in a cycle of fixing brittle ETL and managing unpredictable AI demos. This two-part session provides a blueprint for breaking that cycle by building a data stack that doesn't just move data, but understands it.

Data and AI engineers are trapped in a cycle of fixing brittle ETL and managing unpredictable AI demos. This two-part session provides a blueprint for breaking that cycle by building a data stack that doesn't just move data, but understands it.

Join us for a hands-on session where we'll demonstrate how to build vendor-neutral streaming analytics pipelines using Apache Polaris. Learn how to create portable analytics solutions that work across multiple engines and infrastructures, breaking free from traditional vendor lock-in constraints.

Join us for a hands-on session where we'll demonstrate how to build vendor-neutral streaming analytics pipelines using Apache Polaris. Learn how to create portable analytics solutions that work across multiple engines and infrastructures, breaking free from traditional vendor lock-in constraints.

Data-driven success needs fast analytics, but manual pipeline deployments slow things down. See how organizations transform data operations using software practices in Snowflake engineering. Using terminal-first methods, version-controlled SQL and automated checks, teams cut deployment time while keeping reliability. Learn to implement Git-based changes, data-aware CI/CD, and infrastructure-as-code to speed up insights.