Crucial Exams

AWS Certified Data Engineer Associate DEA-C01 Practice Question

An ecommerce company builds an end-to-end machine learning pipeline on AWS. Raw clickstream data is stored in Amazon S3, processed with AWS Glue jobs, and the resulting features are used to train models in Amazon SageMaker. Compliance teams require an automated way to capture and visualize the complete lineage of datasets, transformations, training jobs, and registered models without writing custom code. Which solution meets these requirements?

  • Configure AWS Glue job bookmarks and table versioning; the bookmarks create a lineage graph in the AWS Glue Data Catalog for all downstream artifacts.

  • Enable Amazon SageMaker ML Lineage Tracking; it automatically records and visualizes relationships among datasets, processing jobs, training jobs, and model artifacts in the SageMaker console.

  • Turn on AWS CloudTrail data events for the S3 buckets and SageMaker; query the events with Amazon Athena to build a lineage dashboard.

  • Enable Lake Formation tag-based access control on the S3 locations; the console displays lineage of data and models based on the assigned tags.

AWS Certified Data Engineer Associate DEA-C01
Data Store Management
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