Data-Engineer-Associate Practice Questions

A.  

ALL distribution

B.  

EVEN distribution

C.  

AUTO distribution

D.  

KEY distribution

A.  

Write a custom extract, transform, and load (ETL) job in Python. Use the DataFramedrop duplicatesf) function by importing the Pandas library to perform data deduplication.

B.  

Write an AWS Glue extract, transform, and load (ETL) job. Use the FindMatches machine learning (ML) transform to transform the data to perform data deduplication.

C.  

Write a custom extract, transform, and load (ETL) job in Python. Import the Python dedupe library. Use the dedupe library to perform data deduplication.

D.  

Write an AWS Glue extract, transform, and load (ETL) job. Import the Python dedupe library. Use the dedupe library to perform data deduplication.

A.  

Modify the AWS Glue job to copy the rows into a staging Redshift table. Add SQL commands to update the existing rows with new values from the staging Redshift table.

B.  

Modify the AWS Glue job to load the previously inserted data into a MySQL database. Perform an upsert operation in the MySQL database. Copy the results to the Amazon Redshift tables.

C.  

Use Apache Spark ' s DataFrame dropDuplicates() API to eliminate duplicates. Write the data to the Redshift tables.

D.  

Use the AWS Glue ResolveChoice built-in transform to select the value of the column from the most recent record.

A.  

Attach an AWS Glue security configuration to the ETL job.

B.  

Configure a data protection policy. Attach the policy to the CloudWatch log group.

C.  

Run an Amazon Macie sensitive data discovery job.

D.  

Call AWS Glue sensitive data detection APIs in the ETL job.

A.  

Create an S3 event notification that has an event type of s3:ObjectCreated:*. Use a filter rule to generate notifications only when the suffix includes .csv. Set the Amazon Resource Name (ARN) of the Lambda function as the destination for the event notification.

B.  

Create an S3 event notification that has an event type of s3:ObjectTagging:* for objects that have a tag set to .csv. Set the Amazon Resource Name (ARN) of the Lambda function as the destination for the event notification.

C.  

Create an S3 event notification that has an event type of s3:*. Use a filter rule to generate notifications only when the suffix includes .csv. Set the Amazon Resource Name (ARN) of the Lambda function as the destination for the event notification.

D.  

Create an S3 event notification that has an event type of s3:ObjectCreated:*. Use a filter rule to generate notifications only when the suffix includes .csv. Set an Amazon Simple Notification Service (Amazon SNS) topic as the destination for the event notification. Subscribe the Lambda function to the SNS topic.

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.

A.  

Use Avro format. Use AWS Glue Data Catalog to track schema changes.

B.  

Use ORC format. Use AWS Glue Data Catalog to track schema changes.

C.  

Use Apache Parquet format. Use an external Amazon DynamoDB table to track schema changes.

D.  

Use Apache Parquet format. Use AWS Glue Data Catalog to track schema changes.

E.  

Use ORC format. Store schema definitions in separate files in Amazon S3.

A.  

Configure an S3 Event Notifications rule for all activities on the transactions S3 bucket to invoke an AWS Lambda function. Program the Lambda function to write the event to Amazon Kinesis Data Firehose. Configure Kinesis Data Firehose to write the event to the logs S3 bucket.

B.  

Create a trail of management events in AWS CloudTraiL. Configure the trail to receive data from the transactions S3 bucket. Specify an empty prefix and write-only events. Specify the logs S3 bucket as the destination bucket.

C.  

Configure an S3 Event Notifications rule for all activities on the transactions S3 bucket to invoke an AWS Lambda function. Program the Lambda function to write the events to the logs S3 bucket.

D.  

Create a trail of data events in AWS CloudTraiL. Configure the trail to receive data from the transactions S3 bucket. Specify an empty prefix and write-only events. Specify the logs S3 bucket as the destination bucket.

A.  

Use a provisioned Amazon EMR cluster after normal business hours to process the previous day’s data, apply all necessary transformations, and load the prepared data into Amazon Redshift Serverless.

B.  

Use an AWS Glue Flex job after normal business hours to process the previous day’s data, apply all necessary transformations, and load the prepared data into Amazon Redshift Serverless.

C.  

Use an AWS Lambda function after normal business hours to process the previous day’s data, apply all necessary transformations, and load the prepared data into an Amazon Redshift provisioned cluster.

D.  

Use an AWS Glue Flex job after normal business hours to process the previous day’s data, apply all necessary transformations, and load the prepared data into an Amazon Redshift provisioned cluster.

A.  

Use AWS DataSync to replicate data from the on-premises servers to Amazon Elastic File System (Amazon EFS). Configure automatic backups in AWS Backup.

B.  

Use the Amazon Kinesis Agent on the on-premises servers to send data to Amazon Data Firehose. Store the data in an Amazon S3 bucket that has versioning enabled.

C.  

Use AWS Glue jobs to ingest data from the on-premises servers into Amazon RDS. Enable automated backups for data protection.

D.  

Use a self-managed Apache Kafka agent on the on-premises servers to stream data to Amazon Managed Streaming for Apache Kafka (Amazon MSK). Store the data in an Amazon S3 bucket with versioning enabled.