In March 2025, AWS introduced the overall availability of the following era of Amazon SageMaker, together with Amazon SageMaker Unified Studio, a single knowledge and AI growth setting that brings collectively the performance and instruments from present AWS Analytics and AI/ML providers, together with Amazon EMR, AWS Glue, Amazon Athena, Amazon Redshift, Amazon Bedrock, and Amazon SageMaker AI. You’ll be able to uncover knowledge and AI belongings from throughout your group, then work collectively in initiatives to securely construct and share analytics and AI artifacts, together with knowledge, fashions, and generative AI purposes in a trusted and safe setting. Governance options together with fine-grained entry management are constructed into Amazon SageMaker Unified Studio utilizing Amazon SageMaker Catalog that can assist you meet enterprise safety necessities throughout your whole knowledge property. Unified entry to your knowledge is offered by a unified, open, and safe knowledge lakehouse structure constructed on Apache Iceberg open requirements. Whether or not your knowledge is saved in Amazon Easy Storage Service (Amazon S3) knowledge lakes, Amazon Redshift knowledge warehouses, or third-party and federated knowledge sources, you may entry it from one place and use it with Iceberg-compatible engines and instruments.
AWS for Monetary Companies is a pioneer on the intersection of monetary providers and expertise, enabling our prospects to optimize operations and push the boundaries of innovation with the broadest set of providers and accomplice options—all whereas sustaining safety, compliance, and resilience at scale. Monetary establishments are utilizing AI and machine studying (ML), and generative AI providers on AWS to rework their organizations sooner and in methods by no means earlier than potential. With Amazon SageMaker Unified Studio, monetary providers business (FSI) prospects can seamlessly work throughout totally different compute sources and clusters utilizing unified notebooks, together with generative AI–powered troubleshooting capabilities, and use the built-in SQL editor to question knowledge saved in knowledge lakes, knowledge warehouses, databases, and purposes.
Workshops
On this submit, we’re excited to announce the discharge of 4 Amazon SageMaker Unified Studio publicly accessible workshops which can be particular to every FSI phase: insurance coverage, banking, capital markets, and funds. These workshops may also help you discover ways to deploy Amazon SageMaker Unified Studio successfully for enterprise use circumstances. Comply with the hyperlinks for every FSI use case listed within the following desk to get began for these self-paced workshops.
| FSI use case | Description |
| Insurance coverage | On this workshop, you’ll use Amazon SageMaker Unified Studio and analytics providers to rework your insurance coverage enterprise challenges into alternatives. It gives hands-on expertise in creating data-driven, generative AI–powered options for insurance coverage that ship measurable enterprise worth. |
| Banking | On this workshop, you’ll discover how main retail banks can unlock enterprise worth by utilizing Amazon SageMaker Unified Studio to construct, scale, and govern end-to-end knowledge analytics and ML workflows. The workshop walks you thru a reference structure and curated banking-specific datasets overlaying widespread retail banking use circumstances, resembling buyer segmentation, fraud detection, churn prediction, and generative AI purposes like personalised communication. |
| Capital Markets | On this workshop, you’ll use Amazon SageMaker Unified Studio to investigate commerce and quote knowledge for the S&P 500 shares to generate insights. The information is saved in varied codecs throughout totally different sources. This answer will unify the information from disparate sources utilizing a lakehouse structure and provide workforce members flexibility to entry the information utilizing acquainted SQL constructs. |
| Funds | On this workshop, you’ll use Amazon SageMaker Unified Studio and analytics providers to allow organizations to ingest, retailer, course of, and analyze fee knowledge, supporting wants from knowledge ingestion and storage to huge knowledge analytics, streaming analytics, enterprise intelligence, and machine studying. |
Conclusion
We recognize your feedback and suggestions to assist us speed up adoption of Amazon SageMaker Unified Studio for monetary providers workloads. Contact your AWS account workforce to have interaction a FSI specialist options architect in the event you require extra skilled steerage.
Study extra about AWS for monetary providers, buyer case research, and extra sources on our Monetary Companies web site.