Free DAS-C01 Web TestEngine Demo

Q17 Single choice

A company's data analytics specialist must build a solution to implement quality checks on a dataset before the company uses the data in a sales report. The dataset is stored in an Amazon S3 bucket and is in CSV format.

The data quality checks must include identification of duplicate rows, removal of duplicate rows, and validation of date formats. The solution must run daily and must produce output data in Apache Parquet format in Amazon S3.

Which solution will meet these requirements with the LEAST development effort?

A
Create an AWS Glue ETL job that includes transformation steps to implement data quality checks.
Configure the job to write to Amazon S3. Create a schedule-based job within an AWS Glue workflow to run the job daily.
B
Create an AWS Glue DataBrew job that includes data quality recipe steps to implement data quality checks. Configure the job to write to Amazon S3. Create a schedule within the DataBrew job to run the job daily.
C
Create an Amazon EMR cluster. Use an Apache Spark ETL job that includes data processing steps to implement data quality checks. Configure the job to write to Amazon S3. Create an Apache Oozie workflow to run the job daily.
D
Create an AWS Lambda function. Use custom code to implement data quality checks and to write to Amazon S3. Create an Amazon EventBridge rule to run the Lambda function daily.

DAS-C01 Web TestEngine demo