AWS Big Data Blog
Announcing SageMaker Unified Studio Workshops for Financial Services
In March 2025, AWS announced the general availability of the next generation of Amazon SageMaker, including Amazon SageMaker Unified Studio, a single data and AI development environment that brings together the functionality and tools from existing AWS Analytics and AI/ML services, including Amazon EMR, AWS Glue, Amazon Athena, Amazon Redshift, Amazon Bedrock, and Amazon SageMaker AI. You can discover data and AI assets from across your organization, then work together in projects to securely build and share analytics and AI artifacts, including data, models, and generative AI applications in a trusted and secure environment. Governance features including fine-grained access control are built into Amazon SageMaker Unified Studio using Amazon SageMaker Catalog to help you meet enterprise security requirements across your entire data estate. Unified access to your data is provided by a unified, open, and secure data lakehouse architecture built on Apache Iceberg open standards. Whether your data is stored in Amazon Simple Storage Service (Amazon S3) data lakes, Amazon Redshift data warehouses, or third-party and federated data sources, you can access it from one place and use it with Iceberg-compatible engines and tools.
AWS for Financial Services is a pioneer at the intersection of financial services and technology, enabling our customers to optimize operations and push the boundaries of innovation with the broadest set of services and partner solutions—all while maintaining security, compliance, and resilience at scale. Financial institutions are using AI and machine learning (ML), and generative AI services on AWS to transform their organizations faster and in ways never before possible. With Amazon SageMaker Unified Studio, financial services industry (FSI) customers can seamlessly work across different compute resources and clusters using unified notebooks, including generative AI–powered troubleshooting capabilities, and use the built-in SQL editor to query data stored in data lakes, data warehouses, databases, and applications.
Workshops
In this post, we’re excited to announce the release of four Amazon SageMaker Unified Studio publicly available workshops that are specific to each FSI segment: insurance, banking, capital markets, and payments. These workshops can help you learn how to deploy Amazon SageMaker Unified Studio effectively for business use cases. Follow the links for each FSI use case listed in the following table to get started for these self-paced workshops.
| FSI use case | Description |
| Insurance | In this workshop, you’ll use Amazon SageMaker Unified Studio and analytics services to transform your insurance business challenges into opportunities. It provides hands-on experience in developing data-driven, generative AI–powered solutions for insurance that deliver measurable business value. |
| Banking | In this workshop, you’ll explore how leading retail banks can unlock business value by using Amazon SageMaker Unified Studio to build, scale, and govern end-to-end data analytics and ML workflows. The workshop walks you through a reference architecture and curated banking-specific datasets covering common retail banking use cases, such as customer segmentation, fraud detection, churn prediction, and generative AI applications like personalized communication. |
| Capital Markets | In this workshop, you’ll use Amazon SageMaker Unified Studio to analyze trade and quote data for the S&P 500 stocks to generate insights. The data is stored in various formats across different sources. This solution will unify the data from disparate sources using a lakehouse architecture and offer team members flexibility to access the data using familiar SQL constructs. |
| Payments | In this workshop, you’ll use Amazon SageMaker Unified Studio and analytics services to enable organizations to ingest, store, process, and analyze payment data, supporting needs from data ingestion and storage to big data analytics, streaming analytics, business intelligence, and machine learning. |
Conclusion
We appreciate your comments and feedback to help us accelerate adoption of Amazon SageMaker Unified Studio for financial services workloads. Contact your AWS account team to engage a FSI specialist solutions architect if you require additional expert guidance.
Learn more about AWS for financial services, customer case studies, and additional resources on our Financial Services website.