Oleg Lvovitch

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.

Organizations are building petabyte-scale data lakes on AWS to democratize access to thousands of end users. In this session, learn about recent innovations in Amazon S3 that make it easier to build, secure, and manage your data lakes.

Amazon S3 and Amazon S3 Glacier storage classes provide developers and IT teams with cloud object storage that delivers industry-leading scalability, data availability, security, and performance. This session summarizes Amazon S3 and reviews the S3 storage classes and key features across security, access management, storage management, and more.

Flexibility is key when building and scaling a data lake, and by choosing the right storage architecture, you will have the agility to quickly experiment and migrate to AWS. This session explores best practices for building a data lake on Amazon S3, which allows you to leverage industry-leading AWS, open-source, and third-party analytics and ML tools and gain insights from your data.

Many organizations are racing to become more data driven, and speed to insight is the differentiator. Join this chalk talk to learn how to provide a scalable, cost-effective, and interactive platform for querying large-scale datasets in Amazon S3 using standard SQL.