Amazon SageMaker
The next generation of Amazon SageMaker is the center for all your data, analytics, and AIOverview
Bringing together widely-adopted AWS machine learning 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 (preview) 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, third-party or federated data sources, with governance built-in to meet enterprise security needs.
Benefits
Meet the next generation of Amazon SageMaker
Capabilities
Customers
Toyota
“To address siloed data sets spread across our automotive operations, we are exploring Amazon SageMaker to 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 safety and satisfaction, and accelerate development of generative AI applications.”
– Kamal Distell, VP of Data, Analytics, Platforms, and Data Science, TMNA
NatWest Group
"Our Data Platform Engineering team has been deploying multiple end-user tools for data engineering, ML, SQL, and GenAI 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
Roche
"We have been using Amazon Redshift to gain insights from both structured and semi-structured data across all our data repositories. The new Amazon SageMaker Lakehouse excites me with its potential to enhance and unify access to data lake, and other data sources with services like Amazon Redshift, Glue Data Catalog, and Lake Formation. This innovation will allow our data and engineering teams to simplify data access, promoting interoperability across data, analytics, and application workloads. I foresee a notable reduction in data errors through less data copying, a 40% decrease in processing time, quicker analytics data write-back to transactional systems for improved decision-making, and empowering our teams to focus on creating business value.”
- Yannick Misteli, Head of Engineering, Global Product Strategy, Roche
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 expect to accelerate 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
Natera, Inc
"Our organization has been leveraging Amazon DataZone, Amazon SageMaker AI, Amazon Athena, and Amazon Redshift to manage and analyze our clinical and genomic data. We are excited to now have the unified governance of the Amazon SageMaker Catalog, which will streamline our data discovery and access, enabling our team to quickly analyze relevant data across our whole domain. This integration will help us create tailored datasets, potentially reducing our time-to-insight, and ultimately drive improved patient outcomes as we advance our goal of making personalized genetic testing a standard part of care."
– Mirko Buholzer, VP of Software Engineering, Natera, Inc.