What You Need to Know Before
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Starts 8 June 2025 08:16
Ends 8 June 2025
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Simplify Your Analytics and AI with Amazon SageMaker Lakehouse
Discover how Amazon SageMaker Lakehouse unifies data across S3 lakes and Redshift warehouses, enabling seamless querying with Apache Iceberg tools while maintaining robust security controls.
AWS Events
via YouTube
AWS Events
2544 Courses
20 minutes
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Free Video
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Overview
Discover how Amazon SageMaker Lakehouse unifies data across S3 lakes and Redshift warehouses, enabling seamless querying with Apache Iceberg tools while maintaining robust security controls.
Syllabus
- Introduction to Amazon SageMaker Lakehouse
- Understanding Data Lakes and Data Warehouses
- Apache Iceberg for Seamless Querying
- Integrating Amazon SageMaker Lakehouse
- Data Security and Compliance
- Use Cases and Applications
- Hands-On Workshop
- Performance Optimization
- Conclusion and Next Steps
Overview of data unification on AWS
Key features and benefits
Differences between S3 data lakes and Redshift data warehouses
Use cases for combining data lakes and warehouses
Introduction to Apache Iceberg
Setting up and optimizing Apache Iceberg for data querying
Steps to unify data across S3 and Redshift
Best practices for data management and architecture
Overview of security controls in Amazon SageMaker Lakehouse
Managing access and permissions
Real-world use cases of Amazon SageMaker Lakehouse
Advanced analytics and AI integration
Practical exercises on data unification
Implementing a sample analytics workflow
Techniques for optimizing query performance
Troubleshooting common performance issues
Summary and course review
Additional resources and further learning paths
Subjects
Programming
