Train and deploy AI models with SageMaker AI

Amazon SageMaker

The next generation of Amazon SageMaker is the center for all your data, analytics, and AI

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Overview

Bringing together widely adopted AWS machine learning (ML) and analytics capabilities, Amazon SageMaker delivers an integrated experience for analytics and AI with unified access to all your data. Collaborate and build faster from a unified studio using familiar AWS tools for model development, generative AI, data processing, and SQL analytics, accelerated by Amazon Q Developer, the most capable generative AI assistant for software development. Access all your data whether it’s stored in data lakes, data warehouses, or third-party or federated data sources, with governance built in to meet enterprise security needs.

Benefits

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See the next generation of Amazon SageMaker in action

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Customers

Toyota

"To address siloed data sets spread across our automotive operations, we are implementing Amazon SageMaker to help unify and govern data across our connected car, sales, manufacturing, and supply chain units. This approach allows us to search, discover, and share data effortlessly, laying the groundwork to pre-empt quality issues, increase customer satisfaction, and enable easier development of generative AI applications."

Kamal Distell, VP of Data, Analytics, Platforms, and Data Science, TMNA

Charter Communications

With Amazon SageMaker Unified Studio, you have a one stop shop to interact with various AWS Services, [including] Redshift and SageMaker Lakehouse. It makes the developer experience that much better and improves speed to market because you don’t need to jump across multiple services. Features like Amazon Q Developer are very exciting and we want to explore it further to see how it will help us improve our developer productivity, speed to market, and build better quality solutions.

Senthil Sugumar, Group VP, Business Intelligence, Charter
Communications

Lennar

"We have spent the last 18 months working with AWS to transform our data foundation to use best-in-class solutions that are cost effective as well. With advancements like Amazon SageMaker Unified Studio and Amazon SageMaker Lakehouse, we are accelerating our velocity of delivery through seamless access to data and services, thus enabling our engineers, analysts, and scientists to surface insights that provide material value to our business."

Lee Slezak, SVP of Data and Analytic, Lennar

Carrier

 "At Carrier, the next generation of Amazon SageMaker is transforming our enterprise data strategy by streamlining how we build and scale data products. SageMaker Unified Studio’s approach to data discovery, processing, and model development has significantly accelerated our lakehouse implementation. Most impressively, its seamless integration with our existing data catalog and built-in governance controls enables us to democratize data access while maintaining security standards, helping our teams rapidly deliver advanced analytics and AI solutions across the enterprise."

Justin McDowell, Director of Data Platform & Data Engineering, Carrier

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NatWest Group

"Our Data Platform Engineering team has been deploying multiple end-user tools for data engineering, ML, SQL, and gen AI tasks. As we look to simplify processes across the bank, we’ve been looking at streamlining user authentication and data access authorization. Amazon SageMaker delivers a ready-made user experience to help us deploy one single environment across the organization, reducing the time required for our data users to access new tools by around 50%."

Zachery Anderson, CDAO, NatWest Group

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