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AWS transforms Amazon SageMaker into a single platform for AI and data analytics
- Amazon SageMaker is getting a major update that will integrate faster structured query language analytics, petabyte-scale data processing and more.
- Amazon’s artificial intelligence development platform includes the new SageMaker Unified Studio.
- The SageMaker Unified Studio offers a simplified environment that unifies all the tools found in Amazon’s ecosystem of developer studios, query editors and visual tools.
- It provides access to data from across an organization, as well as a variety of AI and machine learning development tools and the SageMaker Catalog.
- SageMaker is getting its own data platform called SageMaker Lakehouse, which unifies data and includes a giant data repository.
- SageMaker users gain the ability to centralize access to the underlying data assets that power their AI models.
- F. Hoffmann-La Roche AG was able to eliminate data silos and make information easier to access and saw a 40% reduction in data processing times thanks to SageMaker Lakehouse.
- AWS has also announced zero-ETL integrations with various third-party software-as-a-service applications, such as Amazon Aurora MySQL, PostgreSQL and other databases.
- AWS Vice President of Data and AI, Swami Sivasubramanian, explains that the emergence of AI and data analytics combined relies on the need for more interconnected data sources.
- SageMaker brings together all capabilities and features that aim to give customers all the tools they need for direct data processing, SQL analytics, model development and training.
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