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Amazon SageMaker customers
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
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
Natera, Inc.
“By integrating Amazon QuickSight with Amazon SageMaker, our lab operations teams and scientists can now monitor clinical test performance across all sites in real time. We’ve developed unified dashboards that consolidate throughput, quality control metrics, and turnaround times, enabling detailed trend analysis and ongoing performance optimization. Scientists can now perform comprehensive data analysis – from exploratory review to model development – all within a single, integrated environment.”
Mirko Buholzer, VP of Software Engineering, Natera, Inc.
Roche
Roche is a global pioneer in pharmaceuticals and diagnostics focused on advancing science to improve people's lives.
“We have been using Amazon Redshift to gain insights from both structured and semistructured data across all our data repositories. The new Amazon SageMaker Lakehouse excites me with its potential to enhance and unify access to data lakes or other data sources with services like Amazon Redshift, AWS Glue Data Catalog, and AWS 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
HEMA
“The launch of the domain upgrade feature allows us to take the investment from our production Amazon DataZone deployment and utilize it in Amazon SageMaker. Organizationally, we are doing more in the generative AI space and with Amazon SageMaker we can accomplish new use cases that leverage the assets curated through Amazon DataZone. With this feature we also love that both portals remain open at the same time so that we can thoughtfully transition user populations to Amazon SageMaker.”
Tommaso Paracciani, Head of Data & Cloud Platforms at HEMA
MD THINK
“The integration between Amazon SageMaker and Amazon QuickSight will help us streamline how our teams move from data exploration to insights. Our analysts can go from data discovery to building and sharing dashboards through a unified, governed experience. Dashboards are no longer siloed, one-off reports. They’re cataloged, discoverable assets that others can find and access. This has made insight delivery faster, more consistent, and far easier to scale across the business.”
Lingam Chockalingam, Chief Data Architect, Maryland Department of Human Services – MD THINK
Adastra
"We build complex data analytics, ML and GenAI applications with built-in data governance and user-friendly interfaces. Before Amazon SageMaker Unified Studio, deploying multiple tools for our customers' data and information workers was mostly manual and time-consuming, and ensuring a robust data architecture provisioning was a challenge. Now, with Amazon SageMaker Unified Studio, we can deploy a single data worker tool for data engineers and ML scientists. We are also automating data infrastructure deployment, allowing us to simplify the process for our customers and enhance their experience."
Zeeshan Saeed, Chief Technology and Strategy Officer, Adastra
NTT DATA
"When we build data-driven applications for our customers, we want a unified platform where the technologies work together in an integrated way. Amazon SageMaker Unified Studio streamlines our solution delivery processes through comprehensive analytics capabilities, a unified studio experience, and a lakehouse that integrates data management across data warehouses and data lakes. Amazon SageMaker Unified Studio reduces the time-to-value for our customers' data projects by up to 40%, helping us with our mission to accelerate our customers' digital transformation journey."
Akihiro Suzue, Head of Solutions Sector, NTT DATA; Yuji Shono, Senior Manager, Apps & Data Technology Department, NTT DATA; Yuki Saito, Manager, Digital Success Solutions Division, NTT DATA
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
Amazon Transportation
"At Amazon, we continue to improve delivery speeds and increase number of items delivered same day or overnight. To support getting items to customers this fast we rely heavily on data and insights. We are looking to accelerate the process of deriving realtime insights with right access to data with Analytics and AI. Using SageMaker Unified Studio we will be able to accelerate our insights generation from data discovery to building GenAI applications."
Amulya Tayal, Director of Software Development, Amazon Transportation
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
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
Arizona State University
"After evaluating Amazon SageMaker Unified Studio, we immediately recognized its suitability for Arizona State University (ASU) in teaching our students Machine Learning concepts. SageMaker Unified Studio simplifies the integration of various data operations - including data exploration, data processing, feature engineering, and model deployment - into a single experience. This unified approach allows our students, especially those new to ML, to focus more on understanding Machine Learning topics rather than spending time learning to use different tools to construct their Machine Learning pipelines."
John Rome, Deputy Chief Information Officer, Enterprise Technology, Arizona State University
Swiss Life
“The launch of SageMaker Unified Studio comes at the perfect time for Swiss Life. It is a great product that will simplify the main goal: Bring data to the people that really need it. The ability to connect various data sources, easily share them with another team or product and use the full power of the underlying AWS infrastructure will take data science at Swiss Life to the next level.”
Simon Mannstein, Team Lead Cloud Platform & Adoption, Swiss Life Deutschland
Cisco
"You want to discover, share, and govern your data. Whether you call it a data mesh or a data fabric, data exists across different teams in multiple silos, and you need a way to bring it together. Amazon SageMaker Catalog connects data producers and consumers, enabling producers to share data with built-in controls and data contracts while allowing consumers to access the data using the tools of their choice"
Shaja Arul Selvamani, Sr. Director AI/ML, Cisco
Idealista
Idealista supports real estate agents and private individuals across Southern Europe by providing an online real estate classifieds platform.
“Our goal is to streamline access to Salesforce data for enhanced analytics in our data lake. By leveraging the new Amazon SageMaker Lakehouse support for zero-ETL integrations from applications feature, we can simplify our data extraction and ingestion processes, removing the need for multiple ETLs to access Salesforce directly. This centralized approach reduces complexity and significantly improves our data management efficiency. We anticipate a significant time savings in data extraction and ingestion development, allowing our team to focus on deriving actionable insights from our data rather than managing its collection.“
Javier Monterrubio, Data Platform Engineer Manager, Idealista
