Powering Partner Solutions with Next Generation Amazon SageMaker

By Madhu V, WW Partner Lead, Data & AI Governance and Security – AWS
By Sam Anand, WW Partner Lead, Data Foundations for AI – AWS
By Vitor Freitas, WW Tech Lead, Data & AI – AWS
By Vishal Sharma, Sr. Manager, Data & AI PSA – AWS

At re: Invent 2024, AWS unveiled the next generation of Amazon SageMaker (now generally available), a unified platform for Data, Analytics and AI on Amazon Web Services (AWS). Bringing together widely-adopted AWS machine learning and analytics capabilities, the next generation of Amazon SageMaker delivers an integrated experience for analytics and AI with unified access to all your data. These advancements have the potential to transform how businesses and developers build, scale, and deploy analytics and AI applications, unlocking unprecedented opportunities for innovation and efficiency.

This post highlights the next generation Amazon SageMaker and its new features, including a Unified Studio, Lakehouse, and enhanced governance tools, which aim to streamline the entire data and AI workflow. It also provides insights into how AWS Partners can leverage Amazon SageMaker to enhance their solutions.

Amazon SageMaker

Amazon SageMaker is a unified platform that combines various AWS services into a single, integrated experience supporting data analytics and AI workloads. Amazon SageMaker enables you to collaborate and build faster from a unified studio using 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 data, whether stored in data lakes, data warehouses, third party or federated data sources, with governance built-in to address enterprise security needs.

Amazon SageMaker has the following capabilities:

• Amazon SageMaker Unified Studio enables data discovery, preparation, query and code authoring, model development and training, and insights generation—all within a single platform that can bring your entire data team in one tool by integrating functionality from AWS analytics and ML services, known for their price-performance, scalability, and reliability.
• Amazon SageMaker Lakehouse unifies data from Analytics and AI sources, integrating date from Amazon S3 data lakes, Amazon Redshift warehouses, near real-time Zero-ETL from applications and operational databases and federation for third-party access. With an Iceberg API interface and consistent fine-grained controls, it offers a comprehensive, open and secure Data Lakehouse.
• Amazon SageMaker Data & AI Governance simplifies the discovery, governance, and collaboration for data and AI across your lakehouses, AI models, and applications.
• Amazon SageMaker Data Processing and Analytics helps analyze, prepare and integrate data for analytics and AI using open-source frameworks such as Apache Spark, Python and Ray on Amazon Athena, Amazon EMR, AWS Glue and Amazon Managed Workflows for Apache Airflow.
• Amazon SageMaker AI, enables build, train and deploy ML and Foundation Models, with fully managed infrastructure, tools and workflows.
• Amazon Bedrock Integrated Development Experience supports building and scaling Generative AI applications by providing a governed collaborative environment integrated with Amazon SageMaker Unified Studio. It provides access to Foundation Models and additional capabilities like Knowledge Bases, Guardrails, Agents and Flows.
• Amazon Redshift supports seamless integration with Amazon SageMaker Lakehouse and leverages its SQL analytics capabilities on the unified data. It enables near-real time analytics with Redshift Zero-ETL integrations without building complex data pipeline. Also, deployable as Serverless brings in scalability of the solution easily and simplifies SQL authoring through natural language using Amazon Q in Redshift.

Partner Testimonials

Here’s what AWS Partners had to say about Amazon SageMaker’s features, successful customer collaborations, and opportunities to integrate SaaS offerings with Amazon SageMaker to drive customer transformation:

“We build complex data analytics, ML and GenAI applications with built-in data governance and user-friendly interfaces,” says Zeeshan Saeed, Chief Technology and Strategy Officer at Adastra. “Before Amazon SageMaker, deploying multiple tools for our customers’ data and information workers was mostly manual and time-consuming, and ensuring a robust data architecture and infrastructure provisioning was a challenge. Now, with Amazon SageMaker we can deploy a single data worker tool for Data Engineers, ML Scientists, BI and Data Analysts. We will also be able to automate data infrastructure deployment, allowing us to simplify the process for our customers and enhance their experience.”

“Amazon SageMaker brings enhanced capabilities to transform data ecosystems, fostering enterprise AI adoption, all within the boundaries of a strong data governance and operations management,” says Sivaram Sivanarayanan, Global Head of AWS Products & Offerings, AI.Cloud at TCS. “With Amazon Q Developer available across Amazon SageMaker, we see opportunity to boost developer productivity, drive faster data discovery and streamline the overall process.”

“Amazon SageMaker brings a single enterprise-grade foundation that underpins customer use cases across generative AI, AI/ML, and analytical domains, with Amazon Q Developer integrations bringing generative AI assistance throughout,” says Ashwin Patil, Partner, Data Engineering & Analytics Market Offering Leader at Deloitte Consulting. “This unified stack can increase developer productivity and reduce time to delivery by removing overhead associated with using disparate services.”

“Etleap is committed to making real-time, large-scale data ingestion more accessible and cost-effective for our customers,” explains Christian Romming, Founder & CEO at Etleap. “By integrating Amazon SageMaker Lakehouse into our ingestion pipeline, we aim to deliver an innovative solution that reduces latency and optimizes costs. Together, Etleap and Amazon SageMaker Lakehouse have the potential to enable organizations to unlock real-time insights, supporting faster, data-driven decisions with greater efficiency. This launch represents an exciting step forward for the future of data analytics.”

“With Tableflow on Confluent Cloud, organizations can quickly turn data from across the business into Apache Iceberg tables,” says Mike Agnich, General Manager and Vice President of Product Management at Confluent. “The new Amazon SageMaker Lakehouse, together with Tableflow, will provide seamless access to unified data from various sources, enabling our joint customers to build critical applications and downstream analytics that power countless real-time innovations.”

Partner Showcase

We invite you to explore the following AWS Partners who are building solutions using Amazon SageMaker:

AWS Services Partners

AWS Partners using Amazon SageMaker enhance their solution delivery through a unified data platform that reduces implementation time and scales effectively. They leverage advanced AI/ML tools for streamlined data management and innovation, while benefiting from AWS’s robust security controls and improved data governance. The platform’s cost-effectiveness comes from optimized ETL processes and reduced redundancy, while the consistent AWS Cloud accelerates time-to-market.

Partners can expand across industries with versatile solutions that integrate seamlessly with client systems. With AWS’s continuous advancements in automated ML, responsible AI, and global infrastructure, Amazon SageMaker enables Partners to deliver modern, efficient, and compliant solutions.

• Deloitte
• Tata Consultancy Services
• Accenture
• Cognizant
• Infosys
• Capgemini
• Wipro
• Adastra
• NTT Data
• Mantel Group

AWS Software Partners

These AWS Partners have deep expertise using Amazon SageMaker for integration or SaaS product development gain significant advantages, including streamlined product development through seamless integration with AWS Data & AI services, access to a scalable global infrastructure without heavy investment, enhanced security and compliance measures, and cost-effective operational models.

Partners can leverage AWS innovation to differentiate their offerings, tap into new markets via AWS Marketplace, and benefit from simplified data management. This enables ISVs to focus on their core competencies while leveraging AWS advanced capabilities, ultimately leading to more competitive, secure, and innovative products with broader market reach.

• Informatica
• Etleap
• dbt Labs
• Confluent
• Tableau

Customers: Work with an Amazon SageMaker Partner

Amazon SageMaker Partners combine deep expertise in Amazon SageMaker’s comprehensive toolset with proven implementation experience.

From unified data management to AI governance, these specialized Partners help you maximize Amazon SageMaker’s capabilities, including advanced analytics, ML development, and generative AI through Amazon Bedrock.

Work with an Amazon SageMaker Launch Partner to accelerate your data and AI initiatives, and drive business value.

Partners: Become an Amazon SageMaker Partner

Unlock new opportunities and enhance your service offerings by integrating Amazon SageMaker into your solutions portfolio.

Schedule a discovery call with your Partner Development Manager to access exclusive Amazon SageMaker resources and training, receive expert support to build AI/ML solutions, and accelerate your business growth in the rapidly expanding AI and data analytics market.

To learn more, read the following blogs:

• Fuel Generative AI Success: Building Robust Data Foundation with AWS Partners
• Energize and Amplify Data and AI Governance and Security on AWS through Partners