Free Amazon AWS-DEA-C01 Exam Questions

Question 1

A company wants to migrate a data warehouse from Teradata to Amazon Redshift. Which solution will meet this requirement with the LEAST operational effort?

A : Use AWS Database Migration Service (AWS DMS) Schema Conversion to migrate the schema. Use AWS DMS to migrate the data.

B : Use the AWS Schema Conversion Tool (AWS SCT) to migrate the schema. Use AWS Database Migration Service (AWS DMS) to migrate the data.

C : Use AWS Database Migration Service (AWS DMS) to migrate the data. Use automatic schema conversion.

D : Manually export the schema definition from Teradata. Apply the schema to the Amazon Redshift database. Use AWS Database Migration Service (AWS DMS) to migrate the data.

Answer: B

Question 2

A telecommunications company collects network usage data throughout each day at a rate of several thousanddata points each second. The company runs an application to process the usage data in real time. Thecompany aggregates and stores the data in an Amazon Aurora DB instance.Sudden drops in network usage usually indicate a network outage. The company must be able to identifysudden drops in network usage so the company can take immediate remedial actions.Which solution will meet this requirement with the LEAST latency?

A : Create an AWS Lambda function to query Aurora for drops in network usage. Use Amazon EventBridge to automatically invoke the Lambda function every minute.

B : Modify the processing application to publish the data to an Amazon Kinesis data stream. Create an Amazon Managed Service for Apache Flink (previously known as Amazon Kinesis Data Analytics) application to detect drops in network usage.

C : Replace the Aurora database with an Amazon DynamoDB table. Create an AWS Lambda function to query the DynamoDB table for drops in network usage every minute. Use DynamoDB Accelerator (DAX) between the processing application and DynamoDB table.

D : Create an AWS Lambda function within the Database Activity Streams feature of Aurora to detect drops in network usage.

Answer: B

Question 3

A Data Engineering Team is designing a system to manage a series of dependent data processing and transformation jobs. These jobs involve various AWS services, including AWS Lambda for data manipulation, Amazon S3 for data storage, and AWS Glue for ETL operations. The team needs a robust solution to orchestrate these jobs, ensuring that they execute in a specific sequence and with conditional error handling.

Which AWS service should the team use for the most effective orchestration of these data processing workflows?

A : Implement Amazon Managed Workflows for Apache Airflow (MWAA) for managing job sequences and dependencies

B : Use AWS Step Functions to coordinate the various data processing and transformation tasks across different AWS services in a cost-effective manner.

C : Configure Amazon EventBridge to trigger and manage the sequence of data processing jobs efficiently.

D : Utilize AWS Glue Workflows for orchestrating the data processing jobs, focusing on ETL operations.

Answer: B

Question 4

A company wants to migrate an application and an on-premises Apache Kafka server to AWS. Theapplication processes incremental updates that an on-premises Oracle database sends to the Kafka server. Thecompany wants to use the replatform migration strategy instead of the refactor strategy.Which solution will meet these requirements with the LEAST management overhead?

A : Amazon Kinesis Data Streams

B : Amazon Managed Streaming for Apache Kafka (Amazon MSK) provisioned cluster

C : Amazon Data Firehose

D : Amazon Managed Streaming for Apache Kafka (Amazon MSK) Serverless

Answer: D

Question 5

A data engineer has two datasets that contain sales information for multiple cities and states. One dataset is named reference, and the other dataset is named primary. The data engineer needs a solution to determine whether a specific set of values in the city and state columns of the primary dataset exactly match the same specific values in the reference dataset. The data engineer wants to use Data Quality Definition Language (DQDL) rules in an AWS Glue Data Quality job. Which rule will meet these requirements?

A : DatasetMatch "reference" "city->ref_city, state->ref_state" = 1.0

B : ReferentialIntegrity "city,state" "reference.{ref_city,ref_state}" = 1.0

C : DatasetMatch "reference" "city->ref_city, state->ref_state" = 100

D : ReferentialIntegrity "city,state" "reference.{ref_city,ref_state}" = 100

Answer: A