Move Data Forward
These sessions will provide you with the insights, tools and inspiration you need to build and manage a modern data pipeline. You'll learn from experts on topics across data ingestion, transformation, storage, how to enable your organization for data-dependent AI, analytics and more.
Sessions
What's New: Revolutionizing Data Movement with Snowflake Openflow, WN212B
Learn how to bring all your data together with Snowflake Openflow to build with limitless interoperability and deployment flexibility, no matter if it's structured, unstructured, batch or streaming data. Make your integration pipelines ready for AI and the future.
What's New: Scaling Data Pipelines with SQL, dbt Projects, and Python , WN215B
Learn how to efficiently scale and manage data engineering pipelines with Snowflake's latest native capabilities for transformations and orchestration with SQL, Python, and dbt Projects on Snowflake. Join us for new product and feature overviews, best practices, and live demos.
What's New Session: Build a Better Enterprise Lakehouse with Native Support for Apache Iceberg Tables™, WN201B
Rethink how you build open, connected, and governed data lakehouses: integrate any Iceberg REST compatible catalog to Snowflake to securely read from and write to any Iceberg table with Catalog Linked Databases. Unlock insights and AI from semi-structured data with support for VARIANT data types. And enjoy enterprise-grade security with Snowflake's managed service for Apache Polaris™, Snowflake Open Catalog.
Building Open Pipelines: Choose Your Own Adventure, DE215
This session will show customers how to build end-to-end open pipelines in Snowflake with Snowflake Open Catalog and integration service! Join us to choose from open architecture and pipeline options, and you get to decide what we build with. During the demo, we will build an integreation pipeline to ingest data from a source of your choice into an Iceberg table in Snowflake, transform it, register the tables in Open Catalog, and query the data from both Snowflake and a third-party query engine. And here's the real kicker: The audience get to pick the direction we go. Don't miss out this fun, demo session with us.
Easily and Cost-Efficiently Managing Data Transformation Pipelines on Snowflake, DE109
Data engineers often face the challenge of creating complex data transformation pipelines while balancing infrastructure overhead, debugging inefficiencies and cost control. Attendees will learn best practices for building scalable and cost-efficient data transformation pipelines with built-in telemetry enhancing monitoring and debugging capabilities. By leveraging automation and managed services in Snowflake, engineers can focus on delivering insights rather than maintaining infrastructure. Join us to discover how to simplify data pipeline management, optimize costs and improve reliability in modern data ecosystems.
How Booking.com Is Architecting Scalable Python Frameworks for the AI Data Cloud, AR220
Discover how the Booking.com Data DevEx team scales data platforms with Snowflake by integrating PySpark, Iceberg, and an S3‐based architecture. Leveraging an in‐house PySpark SDK, we process hundreds of terabytes daily while synchronizing catalogs, optimizing S3 reads, and ensuring high data quality and performance. Gain practical insights into overcoming technical challenges in large‐scale platform development, migration, and operational excellence, with actionable insights.
The Latest and Greatest on Dynamic Tables, DE225
Come learn the latest features available in Dynamic Tables. You’ll learn about new security and governance features, expanded Iceberg support bringing the power of Dynamic Tables directly to your data lake or lakehouse, and what’s new in observability and performance optimization, among others. You will also hear from a special guest about how Dynamic Tables have delivered business outcomes.
Snowpark Bound: Penske’s Smooth Migration from Databricks, DE203
Unlock optimized performance and cost efficiency! Explore Penske’s successful journey converting Databricks workloads to process 50% faster in Snowpark. This real-world case study will equip you with key technical paradigms and keen insights you’ll need to achieve a frictionless migration for your organization. Deliver a more streamlined and performant data engineering environment that also translates into tangible financial savings through reduced infrastructure costs and optimized compute.