AWS Certified Data Engineer - Associate DEA-C01Demo

By Amazon · Question Mode

QuestionQ200

Data Security and Governance

A retail company uses AWS Glue for extract, transform, and load (ETL) processes on a dataset containing customer-order information. The company wants to implement specific validation rules that ensure data accuracy and consistency.

Which solution meets these requirements?

  • A Use AWS Glue job bookmarks to track the data for accuracy and consistency.
  • B Create custom AWS Glue Data Quality rulesets to define specific data quality checks.
  • C Use the built-in AWS Glue Data Quality transforms for standard data quality validations.
  • D Use AWS Glue Data Catalog to maintain a centralized data schema and metadata repository.
Explanation

AWS Glue Data Quality rulesets use the Data Quality Definition Language (DQDL) to define and evaluate tailored data-quality checks, such as completeness, uniqueness, integrity, and custom SQL-based validations. This directly supports enforcing company-specific accuracy and consistency requirements during AWS Glue data processing.

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