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Amazon Web Services AWS Certified Data Engineer - Associate (DEA-C01) Data-Engineer-Associate Question # 62 Topic 7 Discussion

Amazon Web Services AWS Certified Data Engineer - Associate (DEA-C01) Data-Engineer-Associate Question # 62 Topic 7 Discussion

Data-Engineer-Associate Exam Topic 7 Question 62 Discussion:
Question #: 62
Topic #: 7

A company builds a new data pipeline to process data for business intelligence reports. Users have noticed that data is missing from the reports.

A data engineer needs to add a data quality check for columns that contain null values and for referential integrity at a stage before the data is added to storage.

Which solution will meet these requirements with the LEAST operational overhead?


A.

Use Amazon SageMaker Data Wrangler to create a Data Quality and Insights report.


B.

Use AWS Glue ETL jobs to perform a data quality evaluation transform on the data. Use an IsComplete rule on the requested columns. Use a ReferentialIntegrity rule for each join.


C.

Use AWS Glue ETL jobs to perform a SQL transform on the data to determine whether requested columns contain null values. Use a second SQL transform to check referential integrity.


D.

Use Amazon SageMaker Data Wrangler and a custom Python transform to create custom rules to check for null values and referential integrity.


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