Arun Shanmugam

Open table formats and open-source engines like DuckDB give organizations the freedom to choose the right tool for each workload, from interactive dashboards and exploratory analytics to large-scale data processing, with no lock-in.

Storing JSON as STRING blobs forces a trade-off between schema flexibility and query performance due to expensive runtime parsing. The Iceberg V3 VARIANT type breaks this bottleneck by utilizing a native binary format and "shredded" sub-columns for high-speed, columnar access to nested fields.

In this hands-on workshop, learn how financial institutions can create value using Amazon SageMaker to build, scale, and govern end-to-end data analytics and ML workflows. Work with a banking usecase, covering customer segmentation, fraud detection, churn prediction, personalized communication and document processing.