Anupriti Warade

In the AI-first world, privacy and compliance are nonnegotiable necessities, not optional add-ons. The rapid proliferation of sensitive data, coupled with the increasing reliance on AI and machine learning models, makes it critical to proactively address regulations like HIPAA, PCI-DSS, CCPA and GDPR. Failure to do so not only risks massive regulatory fines but also erodes customer trust. This makes privacy and compliance a strategic priority powered by intelligent automation. In this session, learn about how Snowflake addresses this challenge with Horizon Catalog's Sensitive Data Classification and new AI-driven capabilities for data governance and audit.

Apache Iceberg is the foundation for open lakehouses, but consistent governance and true interoperability remain a challenge. This dedicated session cuts through the noise to detail Horizon Catalog’s competitive differentiation. Learn how bringing Polaris inside Horizon creates a truly open ecosystem and why our Iceberg REST Catalog supports secure read/write access across engines. We showcase our leadership in extending fine-grained governance, including enforcing row and column policies on external engines like Apache Spark. Snowflake Horizon is the only catalog that is fully interoperable, future-proof beyond Iceberg and offers zero lock-in for your evolving AI workloads.

It is critical for data-driven businesses today to manage price performance for streaming, data lakes, analytics, and AI/ML workloads as they grow to petabytes scale. AWS customers are increasingly using Apache Iceberg across their technology stacks as a single source of truth to manage their data.

With Amazon S3 you can cost-effectively store and retrieve any amount of data from anywhere. In this chalk talk, learn best practices for optimizing Amazon S3 costs based on your workload requirements.