vuthanhdatt's Second Brain

Associate-DEA-C01_21

15 min read

Questions and Answers

Question ufiWl4fuwq6KVdcyov4B

Question

A data engineer must orchestrate a series of Amazon Athena queries that will run every day. Each query can run for more than 15 minutes. Which combination of steps will meet these requirements MOST cost-effectively? (Choose two.)

Choices

  • A: Use an AWS Lambda function and the Athena Boto3 client start_query_execution API call to invoke the Athena queries programmatically.
  • B: Create an AWS Step Functions workflow and add two states. Add the first state before the Lambda function. Configure the second state as a Wait state to periodically check whether the Athena query has finished using the Athena Boto3 get_query_execution API call. Configure the workflow to invoke the next query when the current query has finished running.
  • C: Use an AWS Glue Python shell job and the Athena Boto3 client start_query_execution API call to invoke the Athena queries programmatically.
  • D: Use an AWS Glue Python shell script to run a sleep timer that checks every 5 minutes to determine whether the current Athena query has finished running successfully. Configure the Python shell script to invoke the next query when the current query has finished running.
  • E: Use Amazon Managed Workflows for Apache Airflow (Amazon MWAA) to orchestrate the Athena queries in AWS Batch.

Question mou0rOijjMVKHDEU7z5Z

Question

A data engineer wants to orchestrate a set of extract, transform, and load (ETL) jobs that run on AWS. The ETL jobs contain tasks that must run Apache Spark jobs on Amazon EMR, make API calls to Salesforce, and load data into Amazon Redshift.

The ETL jobs need to handle failures and retries automatically. The data engineer needs to use Python to orchestrate the jobs.

Which service will meet these requirements?

Choices

  • A: Amazon Managed Workflows for Apache Airflow (Amazon MWAA)
  • B: AWS Step Functions
  • C: AWS Glue
  • D: Amazon EventBridge

Question A2omQ4JSy3CrcGVNqyed

Question

A data engineer maintains custom Python scripts that perform a data formatting process that many AWS Lambda functions use. When the data engineer needs to modify the Python scripts, the data engineer must manually update all the Lambda functions.

The data engineer requires a less manual way to update the Lambda functions.

Which solution will meet this requirement?

Choices

  • A: Store the custom Python scripts in a shared Amazon S3 bucket. Store a pointer to the custom scripts in the execution context object.
  • B: Package the custom Python scripts into Lambda layers. Apply the Lambda layers to the Lambda functions.
  • C: Store the custom Python scripts in a shared Amazon S3 bucket. Store a pointer to the customer scripts in environment variables.
  • D: Assign the same alias to each Lambda function. Call each Lambda function by specifying the function’s alias.

Question LDjobmz7wVUAn3cPJ2zW

Question

A company stores customer data in an Amazon S3 bucket. Multiple teams in the company want to use the customer data for downstream analysis. The company needs to ensure that the teams do not have access to personally identifiable information (PII) about the customers.

Which solution will meet this requirement with LEAST operational overhead?

Choices

  • A: Use Amazon Macie to create and run a sensitive data discovery job to detect and remove PII.
  • B: Use S3 Object Lambda to access the data, and use Amazon Comprehend to detect and remove PII.
  • C: Use Amazon Data Firehose and Amazon Comprehend to detect and remove PII.
  • D: Use an AWS Glue DataBrew job to store the PII data in a second S3 bucket. Perform analysis on the data that remains in the original S3 bucket.

Question CY0ZKEDRKup1HszKaefN

Question

A company stores its processed data in an S3 bucket. The company has a strict data access policy. The company uses IAM roles to grant teams within the company different levels of access to the S3 bucket.

The company wants to receive notifications when a user violates the data access policy. Each notification must include the username of the user who violated the policy.

Which solution will meet these requirements?

Choices

  • A: Use AWS Config rules to detect violations of the data access policy. Set up compliance alarms.
  • B: Use Amazon CloudWatch metrics to gather object-level metrics. Set up CloudWatch alarms.
  • C: Use AWS CloudTrail to track object-level events for the S3 bucket. Forward events to Amazon CloudWatch to set up CloudWatch alarms.
  • D: Use Amazon S3 server access logs to monitor access to the bucket. Forward the access logs to an Amazon CloudWatch log group. Use metric filters on the log group to set up CloudWatch alarms.

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