***This course was developed by members of AWS Technical Field Communities (TFC), an AWS community of technical experts. The content is intended to complement our standard training curriculum and augment your AWS learning journey. We are aware some courses have accessibility limitations and are working to address. If you require accommodation, please contact [AWS Training and Certification Customer Support](https://support.aws.amazon.com/#/contacts/aws-training).*** This course covers essential components of Amazon SageMaker Unified Studio, including its seamless interface for data analytics and AI tools, integration capabilities across SQL analytics, machine learning, and generative AI development, along with a deep understanding of the lakehouse architecture for unified data management. Students will also learn to implement robust data governance frameworks using Amazon SageMaker's built-in capabilities, ensuring secure and compliant data handling practices. Whether you're a data professional, analytics specialist, or AI developer, this course provides the practical knowledge needed to effectively leverage Amazon SageMaker's unified platform for modern data analytics and AI development workflows.


What you'll learn
Discuss the AWS Well-Architected Framework and how to build database solutions around it.
Identify different data categories, and determine alignment to AWS database services.
Compare and categorize AWS relational and nonrelational database services.
Determine the right database to support a given application requirement.
Details to know
December 2025
1 assignment
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There is 1 module in this course
What's included
1 reading1 assignment
Instructor

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Frequently asked questions
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