Amazon SageMaker Unified Studio
A single data and AI development environment, built on Amazon DataZone
Overview
Amazon SageMaker Unified Studio is a single data and AI development environment where you can find and access all of the data in your organization and act on it using the best tools across any use case. SageMaker Unified Studio brings together the functionality and tools from existing AWS Analytics and AI/ML services, including Amazon EMR, AWS Glue, Amazon Athena, Amazon Redshift, Amazon Bedrock, and Amazon SageMaker AI. From within the unified studio, you can find, access, and query data and AI assets across your organization, then work together in projects to securely build and share analytics and AI artifacts, including data, models, and generative AI applications.
An integrated experience for all your data and AI
Discover your data and put it to work using familiar AWS tools for complete development workflows, including model development, generative AI app development, data processing, and SQL analytics, in a single governed environment. Create or join projects to collaborate with your teams, securely share AI and analytics artifacts, and access your data stored in Amazon Simple Storage Service (Amazon S3), Amazon Redshift, and more data sources through the Amazon SageMaker Lakehouse. As AI and analytics use cases converge, transform how data teams work together with SageMaker Unified Studio.
Use best-in-class tools, no matter the job
Streamline access to familiar tools and functionality from purpose-built AWS analytics and artificial intelligence and machine learning (AI/ML) services like Amazon EMR, AWS Glue, Amazon Athena, Amazon Redshift, Amazon Bedrock, and Amazon SageMaker AI. Build integrated data pipelines with visual extract, transform, and load (ETL) and seamlessly work across different compute resources and clusters using unified notebooks. Use the built-in SQL editor to query data stored in data lakes, data warehouses, databases, and applications.
Train, customize, and deploy AI models at scale
Develop ML and foundation models (FMs) using the fully managed infrastructure, tools, and workflows of SageMaker AI. SageMaker AI offers purpose-built tools and infrastructure for each step of the model lifecycle, including data preparation, training, governance, MLOps, inference, experimentation, pipelines, and model monitoring and evaluation. Choose from a curated selection of partner apps to develop performant AI models quickly and securely.
Rapidly build custom generative AI applications
Efficiently build generative AI applications in a trusted and secure environment using Amazon Bedrock. Choose from a selection of high-performing FMs and advanced customization capabilities like Amazon Bedrock Knowledge Bases, Guardrails, Agents, and Flows. Rapidly tailor and deploy generative AI applications, and share with the built-in catalog for discovery.
Accelerate your data journey with Amazon Q Developer
Use Amazon Q Developer for tasks across your development lifecycle, including discovering data for projects, quickly ramping up on collaborations, and securely building ML models. Chat with Amazon Q Developer to understand and use your data for each project and use case. Streamline your data journey with Amazon Q to author code, generate SQL, integrate data, troubleshoot, and more.
Customers and partners
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
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
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
