Amazon Web Services Data-Engineer-Associate Exam With Confidence Using Practice Dumps

Problem Analysis:

The company uses AWS Glue for ETL pipelines and must enforce data quality checks during pipeline execution.

The goal is to implement quality checks with minimal implementation effort.

Key Considerations:

AWS Glue provides an Evaluate Data Quality transform that allows for defining quality checks directly in the pipeline.

DQDL (Data Quality Definition Language) simplifies the process by allowing declarative rule definitions.

Solution Analysis:

Option A: SQL Transform

SQL queries can implement rules but require manual effort for each rule and do not integrate natively with Glue.

Option B: Evaluate Data Quality Transform + DQDL

AWS Glue’s built-in Evaluate Data Quality transform is designed for this use case.

Allows defining thresholds and rules in DQDL with minimal coding effort.

Option C: Custom Transform with PyDeequ

PyDeequ is a powerful library but adds unnecessary complexity compared to Glue’s native features.

Option D: Custom Transform with Great Expectations

Similar to PyDeequ, Great Expectations adds operational complexity and external dependencies.

Final Recommendation:

Use the Evaluate Data Quality transform with DQDL to implement data quality rules in AWS Glue pipelines.

AWS Glue Data Quality

DQDL Syntax and Examples

AWS Glue Studio Documentation

Amazon Redshift supports Role-Based Access Control (RBAC) to manage access to database objects. RBAC allows administrators to create roles for job functions and assign privileges at the schema, table, or column level based on data sensitivity and user roles.

“RBAC in Amazon Redshift helps manage permissions more efficiently at scale by assigning users to roles that reflect their job function. It simplifies user management and secures access based on job role and data sensitivity.”

– Ace the AWS Certified Data Engineer - Associate Certification - version 2 - apple.pdf

RBAC is preferred over RLS or CLS alone because it offers a more comprehensive and scalable solution across multiple users and permissions.