Free Amazon AWS-DEA-C01 Exam Questions

Question 1

A retail company's Data Engineering Team is tasked with refining their Amazon Redshift cluster to facilitate analysis in a separate testing environment, utilizing the primary cluster's data. The new testing process will engage the secondary cluster for a duration of 3 hours biweekly. The team is evaluating the most cost-effective solution to meet this requirement.

Which method would be the most economical for the company to implement?

A : Export data biweekly from the primary Redshift cluster to Amazon S3. Access this data from the Redshift test cluster via Amazon Redshift Spectrum.

B : Establish a data share between the primary Redshift cluster and the test Redshift cluster, utilizing Amazon Redshift Serverless for the latter.

C : Generate a manual snapshot of the primary Redshift cluster every two weeks and restore this to the test cluster, which should mirror the main cluster's node configuration.

D : Program an operation to transfer data from the primary Redshift cluster to Amazon S3 every two weeks, followed by configuring an AWS Glue job to import the data into the Redshift test cluster.

Answer: B

Question 2

A company uses Amazon S3 as a data lake. The company sets up a data warehouse by using a multi-nodeAmazon Redshift cluster. The company organizes the data files in the data lake based on the data source ofeach data file.The company loads all the data files into one table in the Redshift cluster by using a separate COPY commandfor each data file location. This approach takes a long time to load all the data files into the table. Thecompany must increase the speed of the data ingestion. The company does not want to increase the cost of theprocess.Which solution will meet these requirements?

A : Use a provisioned Amazon EMR cluster to copy all the data files into one folder. Use a COPY command to load the data into Amazon Redshift.

B : Load all the data files in parallel into Amazon Aurora. Run an AWS Glue job to load the data into Amazon Redshift.

C : Use an AWS Glue job to copy all the data files into one folder. Use a COPY command to load the data into Amazon Redshift.

D : Create a manifest file that contains the data file locations. Use a COPY command to load the data into Amazon Redshift.

Answer: D

Question 3

A company has a frontend ReactJS website that uses Amazon API Gateway to invoke REST APIs. The APIs

perform the functionality of the website. A data engineer needs to write a Python script that can be

occasionally invoked through API Gateway. The code must return results to API Gateway.

Which solution will meet these requirements with the LEAST operational overhead?

A : Deploy a custom Python script on an Amazon Elastic Container Service (Amazon ECS) cluster.

B : Create an AWS Lambda Python function with provisioned concurrency.

C : Deploy a custom Python script that can integrate with API Gateway on Amazon Elastic Kubernetes Service (Amazon EKS).

D : Create an AWS Lambda function. Ensure that the function is warm byscheduling an Amazon EventBridge rule to invoke the Lambda function every 5 minutes by usingmock events.

Answer: B

Question 4

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

Question 5

An organization's primary transaction processing system is powered by an Amazon RDS for PostgreSQL database. The workload is write-heavy, which is causing consistently high CPU utilization, leading to performance degradation of the system.

What measures should the data engineer implement to alleviate the CPU load on the RDS instance? (Select TWO.)

A : Enable Amazon RDS Performance Insights to analyze and identify expensive queries contributing to high CPU usage.

B : Implement Amazon ElastiCache to cache frequent queries and decrease the read load on the database.

C : Configure a read replica to offload read operations and reduce the load on the primary instance.

D : Increase the IOPS allocation for the RDS instance to handle the write-heavy workload more efficiently.

E : Scale up the RDS instance to a larger class with more CPU and memory resources.

Answer: A,E