Amazon SageMaker Lakehouse zero-ETL integration simplifies machine learning workflows by replicating data from various data stores in data lakes like Amazon S3 and making it readily available. This integration eliminates the need for complex ETL processes, allowing data scientists to directly query and use data from multiple data sources, such as DynamoDB, Salesforce, Instagram ads, etc., for training and inference. By leveraging this seamless integration, organizations can accelerate ML model development, reduce operational overhead, and ensure real-time access to the latest data.
The following is the high-level architecture diagram of the infrastructure that you’ll create in this Cloud Lab: