Free Amazon AWS-DEA-C01 Exam Questions

Question 1

A Data Engineering Consultant is tasked with establishing a CI/CD pipeline for a data engineering project in AWS. The project involves a multi-stage data processing application, requiring reliable build, test, and deployment phases, and should leverage infrastructure as code for consistency and speed. The team desires a highly automated pipeline, well integrated into the AWS ecosystem, with minimal manual interventions and quick turnaround times for deploying updates.

Which of the following setups would best meet these requirements?

A : Store the code in a GitHub repository, use Travis CI for continuous integration and deployment, Ansible for infrastructure provisioning, and deploy to AWS Elastic Beanstalk for managing application deployment.

B : Implement source control with GitLab, use AWS CodeBuild for build and test, AWS CloudFormation for infrastructure management, and manually deploy using AWS Elastic Container Service (ECS) tasks and services.

C : Utilize AWS CodeCommit for source control, AWS CodeBuild for building the application, AWS CodePipeline for orchestrating the CI/CD process, AWS CloudFormation for infrastructure as code, and AWS CodeDeploy for deploying the application across environments.

D : Adopt AWS CodeCommit for version control, integrate CircleCI for building and testing, use Terraform for infrastructure as code, and script deployment processes using AWS CLI within CircleCI jobs.

Answer: C

Question 2

A Cloud Data Engineering Team is working on a large-scale data analytics project for a retail company. The project involves analyzing sales data across multiple sources, including online transactions, in-store purchases, and third-party vendors.

To ensure that data scientists and analysts can find and access the right data efficiently, the team needs to implement a comprehensive data cataloging solution on AWS.

Which combination of AWS services and features should the data engineering team use to build and maintain an effective data catalog? (Select TWO)

A : Configure Amazon S3 event notifications to trigger AWS Lambda functions that update the data catalog in real-time as new data arrives.

B : Use AWS Glue Data Catalog as a central metadata repository to create a unified view of all data assets.

C : Implement Amazon Elasticsearch Service for indexing and searching metadata to enable quick retrieval of catalog information.

D : Utilize AWS Lake Formation to define data access policies centrally and manage permissions for data catalog entries.

E : Deploy Amazon RDS instances to store metadata about each data source, ensuring ACID compliance and relational organization.

Answer: B,D

Question 3

A photography studio stores its high-resolution image files in an Amazon S3 bucket. Recently, they encountered issues with accidental overwrites of important files. The studio requires a solution to prevent the overwriting and accidental deletion of their images while ensuring that the latest version of a file is readily accessible.

Which single feature should the photography studio enable on their S3 bucket to address this issue effectively?

A : Activate S3 Versioning to maintain multiple versions of each file.

B : Enable S3 Object Lock in compliance mode for strict WORM (Write Once, Read Many) protection.

C : Configure S3 Intelligent-Tiering to manage the storage of the files efficiently.

D : Implement S3 Lifecycle policies to archive older versions of files to S3 Glacier.

Answer: A

Question 4

A Data Engineering Team is working on optimizing a complex query that involves numerous joins and aggregations on a large dataset. The dataset is stored in a graph data structure for which the relationships between entities are as crucial as the entities themselves.

The team is deciding on the most appropriate data structure or AWS service to use for this task to ensure both performance efficiency and query optimization. Which of the following should they consider?

A : Implement the data in an Amazon Neptune graph database, taking advantage of its support for highly connected data and complex traversal queries.

B : Store the data in an Amazon DynamoDB table, using its fast and flexible NoSQL database service to manage the relationships and queries efficiently.

C : Utilize Amazon Redshift, leveraging its columnar storage and massively parallel processing (MPP) architecture to handle complex queries and aggregations efficiently.

D : Opt for an Amazon Elastic MapReduce (EMR) cluster with Apache Spark, using Spark's GraphX library for graph processing and query optimizations on large datasets.

Answer: A

Question 5

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