Free Amazon AWS-DEA-C01 Exam Questions

Question 1

A data engineer wants to orchestrate a set of extract, transform, and load (ETL) jobs that run on AWS. TheETL jobs contain tasks that must run Apache Spark jobs on Amazon EMR, make API calls to Salesforce, andload data into Amazon Redshift.The ETL jobs need to handle failures and retries automatically. The data engineer needs to use Python toorchestrate the jobs.Which service will meet these requirements?

A : Amazon Managed Workflows for Apache Airflow (Amazon MWAA)

B : AWS Step Functions

C : AWS Glue

D : Amazon EventBridge

Answer: A

Question 2

A company has as JSON file that contains personally identifiable information (PIT) data and non-PII data. The company needs to make the data available for querying and analysis. The non-PII data must be available to everyone in the company. The PII data must be available only to a limited group of employees. Which solution will meet these requirements with the LEAST operational overhead?

A : Store the JSON file in an Amazon S3 bucket. Configure AWS Glue to split the file into one file that contains the PII data and one file that contains the non-PII data. Store the output files in separate S3 buckets. Grant the required access to the buckets based on the type of user.

B : Store the JSON file in an Amazon S3 bucket. Use Amazon Macie to identify PII data and to grant access based on the type of user.

C : Store the JSON file in an Amazon S3 bucket. Catalog the file schema in AWS Lake Formation. Use Lake Formation permissions to provide access to the required data based on the type of user.

D : Create two Amazon RDS PostgreSQL databases. Load the PII data and the non-PII data into the separate databases. Grant access to the databases based on the type of user.

Answer: C

Question 3

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 4

A Data Engineering Team is tasked with enhancing the CI/CD workflow of their complex ETL pipeline on AWS. The pipeline involves frequent but varying updates—from minor feature additions to major architectural overhauls. The team uses GitHub for version control and manages a diverse array of AWS resources in their projects.

They require a CI/CD solution that not only automates build and test processes upon each commit but also allows for customizable, condition-based deployment strategies (e.g., deploying only specific branches or tags, or based on commit messages).

Given these requirements, which AWS service or combination of services would be the most effective?

A : AWS Lambda and AWS CodePipeline, where a Lambda function is triggered by GitHub webhooks to determine if the deployment should proceed, followed by CodePipeline managing the build, test, and deployment phases.

B : AWS CodeCommit and AWS CodePipeline, with CodeCommit to replace GitHub for enhanced integration within the AWS ecosystem, and CodePipeline to orchestrate the entire process including condition-based deployments.

C : AWS CodePipeline, integrating both GitHub and AWS CodeBuild. CodePipeline to manage the overall workflow and CodeBuild for the build and testing phases, leveraging pipeline actions for deployment conditions.

D : AWS CodeBuild and AWS CodeDeploy, with CodeBuild handling the build and test processes and CodeDeploy managing advanced deployment strategies based on GitHub webhook events.

Answer: C

Question 5

A company needs to load customer data that comes from a third party into an Amazon Redshift datawarehouse. The company stores order data and product data in the same data warehouse. The company wantsto use the combined dataset to identify potential new customers.A data engineer notices that one of the fields in the source data includes values that are in JSON format.How should the data engineer load the JSON data into the data warehouse with the LEAST effort?

A : Use the SUPER data type to store the data in the Amazon Redshift table.

B : Use AWS Glue to flatten the JSON data and ingest it into the Amazon Redshift table.

C : Use Amazon S3 to store the JSON data. Use Amazon Athena to query the data.

D : Use an AWS Lambda function to flatten the JSON data. Store the data in Amazon S3.

Answer: A