Abhishek Narang

Goldman Sach's Lakehouse platform with Iceberg, allows zero-copy data sharing and iceberg rest catalog integration across vendor engines, and seamlessly manages trust, entitlements and governance across these engines. This session will detail Goldman Sachs' journey in developing an "Iceberg-first" data platform, leveraging Lakehouse architecture and will cover the critical architectural and design choices that underpinned this initiative.

This session demonstrates how Goldman Sachs architected an enterprise-grade open lakehouse with built-in governance by combining Snowflake's advanced data sharing capabilities with an open lakehouse architecture. Discover how this approach solves challenges like data silos and duplication, enabling unprecedented scale and flexibility. We'll explore the core principles of zero-copy sharing and interoperability, and how Apache Iceberg integration and the Horizon Catalog enable secure, multi-engine read and write access. This unified platform breaks down traditional vendor lock-in while maintaining enterprise-grade security and governance controls using Snowflake's Org 2.0 and Zero ETL resharing features.

Data is the backbone of modern decision-making, but centralizing it is only the tip of the iceberg. Entitlements, secure sharing and just-in-time availability are critical challenges to any large-scale platform. Join Goldman Sachs as we reveal how our Legend Lakehouse, coupled with Databricks, overcomes these hurdles to deliver high-quality, governed data at scale. By leveraging an open table format (Apache Iceberg) and open catalog format (Unity Catalog), we ensure platform interoperability and vendor neutrality. Databricks Unity Catalog then provides a robust entitlement system that aligns with our data contracts, ensuring consistent access control across producer and consumer workspaces. Finally, Legend functions, integrating with Databricks User Defined Functions (UDF), offer real-time data enrichment and secure transformations without exposing raw datasets. Discover how these components unite to streamline analytics, bolster governance and power innovation.

Financial institutions rely on data for decision-making, but simply centralizing it for analytics is just the tip of the iceberg. The true challenges lie in effective data storage, quality assurance, access control, seamless sharing and consumption, and timely notifications for downstream processes. Our Legend Lakehouse solution directly addresses these complexities. Join us for a discussion about how Goldman Sachs utilizes Apache Iceberg and Snowflake, Legend data models, functions and SDLC to build a secure and highly governed open lakehouse.

Learn how global organization admins on Snowflake can use a range of new organization-level objects to manage Snowflake at scale for their accounts across regions and clouds. Hear about new use cases, such as data sharing and an internal marketplace, that these capabilities enable and hear about what's next on the roadmap.