Data-Engineer-Associate Exam Dumps - AWS Certified Data Engineer - Associate (DEA-C01)

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Question # 73

A company uses AWS Glue ETL pipelines to process data. The company uses Amazon Athena to analyze data in an Amazon S3 bucket.

To better understand shipping timelines, the company decides to collect and store shipping dates and delivery dates in addition to order data. The company adds a data quality check to ensure that the shipping date is later than the order date and that the delivery date is later than the shipping date. Orders that fail the quality check must be stored in a second Amazon S3 bucket.

Which solution will meet these requirements in the MOST cost-effective way?

Use AWS Glue DataBrew DATEDIFF functions to create two additional columns. Validate the new columns. Write failed records to a second S3 bucket.

Use Amazon Athena to query the three date columns and compare the values. Export failed records to a second S3 bucket.

Use AWS Glue Data Quality to create a custom rule that validates the three date columns. Route records that fail the rule to a second S3 bucket.

Use an AWS Glue crawler to populate the AWS Glue Data Catalog. Use the three date columns to create a filter.

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Question # 74

A company is developing machine learning (ML) models. A data engineer needs to apply data quality rules to training data. The company stores the training data in an Amazon S3 bucket.

Create an AWS Lambda function to check data quality and to raise exceptions in the code.

Create an AWS Glue DataBrew project for the data in the S3 bucket. Create a ruleset for the data quality rules. Create a profile job to run the data quality rules. Use Amazon EventBridge to run the profile job when data is added to the S3 bucket.

Create an Amazon EMR provisioned cluster. Add a Python data quality package.

Create AWS Lambda functions to evaluate data quality rules and orchestrate with AWS Step Functions.

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Question # 75

A company needs to collect logs for an Amazon RDS for MySQL database and make the logs available for audits. The logs must track each user that modifies data in the database or makes changes to the database instance.

Which solution will meet these requirements?

Enable Amazon CloudWatch Logs. Create metric filters to monitor database changes and instance-level changes. Configure automated notification systems to send near real-time alerts for suspicious database operations.

Configure an Amazon EventBridge rule to monitor database activity. Create an AWS Lambda function to process EventBridge events and store them in Amazon OpenSearch Service.

Configure AWS CloudTrail to log API calls. Use Amazon CloudWatch Logs for basic monitoring. Use IAM policies to control access to the logs. Set up scheduled reporting for log audits.

Enable and configure native Amazon RDS database audit logging. Enable Amazon CloudWatch Logs. Configure metric filters and alarms. Configure AWS CloudTrail audit logging.

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