AWS unveils next-gen SageMaker for unified AI solutions

Amazon Web Services (AWS) has announced a new generation of its Amazon SageMaker platform, aiming to provide a unified solution for data, analytics, and artificial intelligence (AI).

The updated SageMaker platform features the new SageMaker Unified Studio, which helps users access data within their organisation and combines features from AWS analytics, machine learning, and AI to manage various data use cases efficiently. This unified approach is further supported by tools such as the SageMaker Catalog, which provides built-in governance to ensure that data, models, and development artifacts are accessible only to authorised users.

Remarkably, the SageMaker Lakehouse offers enhanced integration of data across different storage solutions like data lakes, warehouses, and enterprise applications. It also features new zero-ETL integrations, simplifying access to data from third-party SaaS applications directly within the SageMaker environment.

Swami Sivasubramanian, Vice President of Data and AI at AWS, commented on the platform's enhancements: "We are seeing a convergence of analytics and AI, with customers using data in increasingly interconnected ways—from historical analytics to ML model training and generative AI applications. To support these workloads, many customers already use combinations of our purpose-built analytics and ML tools, such as Amazon SageMaker—the de facto standard for working with data and building ML models—Amazon EMR, Amazon Redshift, Amazon S3 data lakes, and AWS Glue. The next generation of SageMaker brings together these capabilities—along with some exciting new features—to give customers all the tools they need for data processing, SQL analytics, ML model development and training, and generative AI, directly within SageMaker."

NatWest Group, a bank in the United Kingdom serving over 19 million customers, expects that the new SageMaker Unified Studio will reduce the time its data users need to access analytics and AI capabilities by 50%, thereby allowing more focus on innovation. According to AWS, this platform will enable NatWest Group to manage its extensive data operations in a single environment, simplifying processes and streamlining efforts across the organisation.

In terms of data and AI governance, the new generation of SageMaker includes SageMaker Catalog, which is built on Amazon DataZone. The feature allows user access policies to be defined consistently across applications, helping secure data and easing the control of permissions and safeguards surrounding AI applications.

SageMaker Lakehouse aims to eliminate data silos by consolidating data stored across Amazon S3, Redshift, and other federated sources, offering a uniform approach to accessing any data from within SageMaker Unified Studio. This unification is expected to reduce data processing time significantly across various industries, as illustrated by Roche—a healthcare specialist utilising SageMaker Lakehouse to integrate data from Redshift and Amazon S3, anticipating a 40% reduction in data processing time.

In terms of easing data access, AWS's zero-ETL integrations for applications such as Zendesk and SAP further reduce the complexity of data exchange, eliminating dependency on cumbersome data pipelines. Organisations including Infosys, Intuit, and Woolworths are already leveraging these integrations for hassle-free data connectivity.

Furthermore, online real estate platform idealista is set to benefit from AWS zero-ETL integrations by simplifying its data extraction processes. This shift will allow the company to focus resources on deriving actionable insights rather than managing data infrastructure.