HomeBig DataSaying SageMaker Unified Studio Workshops for Monetary Companies

Saying SageMaker Unified Studio Workshops for Monetary Companies


In March 2025, AWS introduced the overall availability of the following era of Amazon SageMaker, together with Amazon SageMaker Unified Studio, a single information and AI growth surroundings that brings collectively the performance and instruments from current AWS Analytics and AI/ML companies, together with Amazon EMR, AWS Glue, Amazon Athena, Amazon Redshift, Amazon Bedrock, and Amazon SageMaker AI. You’ll be able to uncover information and AI belongings from throughout your group, then work collectively in tasks to securely construct and share analytics and AI artifacts, together with information, fashions, and generative AI purposes in a trusted and safe surroundings. 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 total information property. Unified entry to your information is offered by a unified, open, and safe information lakehouse structure constructed on Apache Iceberg open requirements. Whether or not your information is saved in Amazon Easy Storage Service (Amazon S3) information lakes, Amazon Redshift information warehouses, or third-party and federated information 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 economic companies and know-how, enabling our prospects to optimize operations and push the boundaries of innovation with the broadest set of companies and accomplice options—all whereas sustaining safety, compliance, and resilience at scale. Monetary establishments are utilizing AI and machine studying (ML), and generative AI companies on AWS to rework their organizations quicker and in methods by no means earlier than doable. With Amazon SageMaker Unified Studio, monetary companies business (FSI) prospects can seamlessly work throughout completely different compute assets and clusters utilizing unified notebooks, together with generative AI–powered troubleshooting capabilities, and use the built-in SQL editor to question information saved in information lakes, information warehouses, databases, and purposes.

Workshops

On this publish, we’re excited to announce the discharge of 4 Amazon SageMaker Unified Studio publicly out there workshops which can be particular to every FSI section: insurance coverage, banking, capital markets, and funds. These workshops might help you discover ways to deploy Amazon SageMaker Unified Studio successfully for enterprise use instances. 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 companies to rework your insurance coverage enterprise challenges into alternatives. It gives hands-on expertise in growing 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 information analytics and ML workflows. The workshop walks you thru a reference structure and curated banking-specific datasets protecting frequent retail banking use instances, reminiscent of buyer segmentation, fraud detection, churn prediction, and generative AI purposes like customized communication.
Capital Markets On this workshop, you’ll use Amazon SageMaker Unified Studio to investigate commerce and quote information for the S&P 500 shares to generate insights. The information is saved in varied codecs throughout completely different sources. This resolution will unify the information from disparate sources utilizing a lakehouse structure and supply crew members flexibility to entry the information utilizing acquainted SQL constructs.
Funds On this workshop, you’ll use Amazon SageMaker Unified Studio and analytics companies to allow organizations to ingest, retailer, course of, and analyze cost information, supporting wants from information ingestion and storage to huge information analytics, streaming analytics, enterprise intelligence, and machine studying.

Conclusion

We admire your feedback and suggestions to assist us speed up adoption of Amazon SageMaker Unified Studio for monetary companies workloads. Contact your AWS account crew to have interaction a FSI specialist options architect if you happen to require further professional steerage.

Study extra about AWS for monetary companies, buyer case research, and extra assets on our Monetary Companies web site.


Concerning the authors

Sanjay Ohri

Sanjay Ohri

Sanjay is an award-winning skilled with over 15 years of profitable international supply and program administration of cost-efficient cloud and on-premise companies to corporations like JPMorganChase and Financial institution of America. He works at AWS as a Principal Supervisor inside Worldwide Monetary Companies working carefully with prospects and product groups serving to to speed up adoption of AWS companies.

Raghu Prabhu

Raghu Prabhu

Raghu is an skilled info know-how government with a profitable monitor report of implementing giant know-how initiatives. He has designed and managed execution of company IT methods, product growth, giant mergers and acquisitions, information heart consolidations, cloud system implementations, legacy system conversions and enterprise course of. He works at AWS as a Go-To-Market Specialist for SageMaker Unified Studio.

RELATED ARTICLES

LEAVE A REPLY

Please enter your comment!
Please enter your name here

- Advertisment -
Google search engine

Most Popular

Recent Comments