Free DEA-C01 exam questions in PDF & AI Tutor

QUESTION: 1

A data engineer is configuring an AWS Glue job to read data from an Amazon S3 bucket. The data engineer has set up the necessary AWS Glue connection details and an associated IAM role. However, when the data engineer attempts to run the AWS Glue job, the data engineer receives an error message that indicates that there are problems with the Amazon S3 VPC gateway endpoint.
The data engineer must resolve the error and connect the AWS Glue job to the S3 bucket.
Which solution will meet this requirement?

Update the AWS Glue security group to allow inbound traffic from the Amazon S3 VPC gateway endpoint.
Configure an S3 bucket policy to explicitly grant the AWS Glue job permissions to access the S3 bucket.
Review the AWS Glue job code to ensure that the AWS Glue connection details include a fully qualified domain name.
Verify that the VPC's route table includes inbound and outbound routes for the Amazon S3 VPC gateway endpoint.

Answer(s): D

Explanation:

The correct answer is D because ensuring the VPC route table contains routes to the S3 VPC gateway endpoint is essential for private connectivity from Glue to S3 without internet access, resolving gateway endpoint issues.
A is incorrect because security groups for Glue do not manage VPC endpoint connectivity to S3; gateway endpoints are routed via route tables, not inbound SG rules for S3 access.
B is incorrect because bucket policies control object-level permissions, not the network path or endpoint configuration needed for VPC gateway endpoint connectivity.
C is incorrect because the issue is network routing to the gateway endpoint, not the domain name resolution in the Glue connection details.

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QUESTION: 2

A retail company has a customer data hub in an Amazon S3 bucket. Employees from many countries use the data hub to support company-wide analytics. A governance team must ensure that the company's data analysts can access data only for customers who are within the same country as the analysts.
Which solution will meet these requirements with the LEAST operational effort?

Create a separate table for each country's customer data. Provide access to each analyst based on the country that the analyst serves.
Register the S3 bucket as a data lake location in AWS Lake Formation. Use the Lake Formation row-level security features to enforce the company's access policies.
Move the data to AWS Regions that are close to the countries where the customers are. Provide access to each analyst based on the country that the analyst serves.
Load the data into Amazon Redshift. Create a view for each country. Create separate IAM roles for each country to provide access to data from each country. Assign the appropriate roles to the analysts.

Answer(s): B

Explanation:

A short, scalable access control is achieved by using Lake Formation with row-level security on an S3 data lake location. This enforces per-country data access without duplicating data or managing multiple catalogs.
A) Creating separate tables per country adds data silos and manual access management; increases maintenance and operational overhead.
C) Moving data to regionalized storage does not inherently restrict access; it complicates data access governance and may trigger data transfer concerns.
D) Redshift-based solution involves data duplication, complex IAM role management, and per-country views, increasing operational burden.
B) Lake Formation provides centralized, policy-based row-level security for S3 data with minimal manual administration.

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QUESTION: 3

A media company wants to improve a system that recommends media content to customer based on user behavior and preferences. To improve the recommendation system, the company needs to incorporate insights from third-party datasets into the company's existing analytics platform.
The company wants to minimize the effort and time required to incorporate third-party datasets.
Which solution will meet these requirements with the LEAST operational overhead?

Use API calls to access and integrate third-party datasets from AWS Data Exchange.
Use API calls to access and integrate third-party datasets from AWS DataSync.
Use Amazon Kinesis Data Streams to access and integrate third-party datasets from AWS CodeCommit repositories.
Use Amazon Kinesis Data Streams to access and integrate third-party datasets from Amazon Elastic Container Registry (Amazon ECR).

Answer(s): A

Explanation:

AWS Data Exchange allows subscribing to third-party datasets and integrates them with minimal operational overhead and automated data refreshes, aligning with the requirement to minimize effort/time. A) Correct: provides managed data access via API, reducing ETL setup. B) DataSync is for automated on-premises/cloud data movement, not third-party data cataloging; it adds integration overhead. C) Kinesis Data Streams requires building ingestion from CodeCommit repositories, increasing complexity and maintenance. D) Kinesis Data Streams with ECR is unrelated to pulling third-party datasets; ECR is for container images, not data ingestion.

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QUESTION: 4

A financial company wants to implement a data mesh. The data mesh must support centralized data governance, data analysis, and data access control. The company has decided to use AWS Glue for data catalogs and extract, transform, and load (ETL) operations.
Which combination of AWS services will implement a data mesh? (Choose two.)

Use Amazon Aurora for data storage. Use an Amazon Redshift provisioned cluster for data analysis.
Use Amazon S3 for data storage. Use Amazon Athena for data analysis.
Use AWS Glue DataBrew for centralized data governance and access control.
Use Amazon RDS for data storage. Use Amazon EMR for data analysis.
Use AWS Lake Formation for centralized data governance and access control.

Answer(s): B,E

Explanation:

A data mesh with centralized governance and access control aligns with S3 as storage and Athena for analysis, enabling data product thinking across domains while serverless query and catalog integration. Option B correctly pairs a data lake (S3) with serverless analytics (Athena) suitable for a mesh approach. Option E correctly brings in AWS Lake Formation to centralize governance and access control for data in S3, fulfilling governance requirements across domains.
A) Aurora and Redshift are traditional operational/analytic engines but do not inherently support mesh governance or centralized access control across domains. C) Glue DataBrew focuses on preparation, not centralized governance. D) RDS/EMR do not directly provide centralized governance and access control for a mesh.

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QUESTION: 5

A data engineer maintains custom Python scripts that perform a data formatting process that many AWS Lambda functions use. When the data engineer needs to modify the Python scripts, the data engineer must manually update all the Lambda functions.
The data engineer requires a less manual way to update the Lambda functions.
Which solution will meet this requirement?

Store a pointer to the custom Python scripts in the execution context object in a shared Amazon S3 bucket.
Package the custom Python scripts into Lambda layers. Apply the Lambda layers to the Lambda functions.
Store a pointer to the custom Python scripts in environment variables in a shared Amazon S3 bucket.
Assign the same alias to each Lambda function. Call reach Lambda function by specifying the function's alias.

Answer(s): B

Explanation:

A concise explanation: Packaging the shared Python scripts into Lambda layers and applying the layers to the Lambda functions centralizes the script versioning; updating the layer updates all functions that reference it without modifying each function. A) Pointer in execution context is not a durable, scalable mechanism and does not enforce consistent updates. C) Environment variables pointing to a script in S3 still requires manual updates to multiple functions if the path or version changes. D) Using aliases does not propagate code updates; aliases route to different versions, but code changes require new versions and redeployments. B) provides centralized, reusable code management across multiple Lambdas.

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QUESTION: 6

A company created an extract, transform, and load (ETL) data pipeline in AWS Glue. A data engineer must crawl a table that is in Microsoft SQL Server. The data engineer needs to extract, transform, and load the output of the crawl to an Amazon S3 bucket. The data engineer also must orchestrate the data pipeline.
Which AWS service or feature will meet these requirements MOST cost-effectively?

AWS Step Functions
AWS Glue workflows
AWS Glue Studio
Amazon Managed Workflows for Apache Airflow (Amazon MWAA)

Answer(s): B

Explanation:

A) AWS Step Functions
B) AWS Glue workflows
C) AWS Glue Studio
D) Amazon Managed Workflows for Apache Airflow (Amazon MWAA)
AWS Glue workflows is correct because it coordinates ETL jobs, crawlers, and data transformations within a single cost-effective, serverless Glue environment, ideal for crawling SQL Server data, transforming, and loading to S3, plus native orchestration of Glue jobs and crawlers. Step Functions can orchestrate but adds extra state management and may incur higher overhead. Glue Studio is a UI for authoring jobs but not the orchestration backbone for multiple Glue components. Amazon MWAA is an external Airflow service with higher management overhead and cost for simple Glue-based pipelines.

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QUESTION: 7

A financial services company stores financial data in Amazon Redshift. A data engineer wants to run real-time queries on the financial data to support a web-based trading application. The data engineer wants to run the queries from within the trading application.
Which solution will meet these requirements with the LEAST operational overhead?

Establish WebSocket connections to Amazon Redshift.
Use the Amazon Redshift Data API.
Set up Java Database Connectivity (JDBC) connections to Amazon Redshift.
Store frequently accessed data in Amazon S3. Use Amazon S3 Select to run the queries.

Answer(s): B

Explanation:

Real-time query capability with minimal operational overhead is achieved by the Redshift Data API, which enables SQL queries from applications over HTTPS without managing database connections or drivers.
A) WebSocket connections to Redshift are not a managed, serverless API and require ongoing connection handling.
B) Redshift Data API provides serverless, stateless access suitable for web apps, reducing connection management.
C) JDBC connections require managing connection pools and drivers, adding operational burden.
D) S3 Select queries on data in S3 do not directly query Redshift data and are not suitable for real-time, transactional querying needs.

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QUESTION: 8

A company uses Amazon Athena for one-time queries against data that is in Amazon S3. The company has several use cases. The company must implement permission controls to separate query processes and access to query history among users, teams, and applications that are in the same AWS account.
Which solution will meet these requirements?

Create an S3 bucket for each use case. Create an S3 bucket policy that grants permissions to appropriate individual IAM users. Apply the S3 bucket policy to the S3 bucket.
Create an Athena workgroup for each use case. Apply tags to the workgroup. Create an IAM policy that uses the tags to apply appropriate permissions to the workgroup.
Create an IAM role for each use case. Assign appropriate permissions to the role for each use case. Associate the role with Athena.
Create an AWS Glue Data Catalog resource policy that grants permissions to appropriate individual IAM users for each use case. Apply the resource policy to the specific tables that Athena uses.

Answer(s): B

Explanation:

Athena workgroups with tags enable separate permission scopes for query execution and query history per use case, allowing granular control via IAM policies tied to those tags.
A) Incorrect: Creating separate S3 buckets and policies mixes storage isolation with query access; it’s not scalable for managing Athena query history or per-use-case access across users/teams.
C) Incorrect: Per-use-case IAM roles require explicit role assumption management for each user/application and do not natively partition query history within Athena across cases.
D) Incorrect: Glue Data Catalog resource policies control access to catalogs, not per-use-case query execution or history in Athena; it doesn’t granularly partition by use case.

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What the DEA-C01 Exam Tests and How to Pass It

The AWS Certified Data Engineer - Associate DEA-C01 certification is designed for professionals who are responsible for building, maintaining, and managing data pipelines and data stores within the Amazon Web Services ecosystem. This certification validates a candidate's ability to implement data ingestion, transformation, and storage solutions that are secure, scalable, and cost-effective. Organizations hiring for roles such as Data Engineer, ETL Developer, or Cloud Data Architect look for this credential to ensure that potential employees possess the technical proficiency required to handle complex data workflows. By passing this certification exam, you demonstrate that you have the foundational knowledge to support data-driven decision-making processes using Amazon’s suite of data services. It is a critical benchmark for anyone looking to specialize in the cloud data engineering space, as it confirms your capability to operate within the specific constraints and best practices defined by Amazon.

The professional function of a certified AWS Data Engineer involves more than just writing code; it requires a deep understanding of how various AWS services interact to create a cohesive data architecture. Employers value this certification because it serves as a reliable indicator that a candidate understands the nuances of data lifecycle management, from the initial ingestion of raw data to the final delivery of insights. Whether you are working in a startup or a large enterprise, the skills validated by this Amazon certification are essential for maintaining the integrity and availability of data systems. As businesses increasingly rely on cloud-native data solutions, the demand for professionals who can navigate the complexities of AWS data services continues to grow. Achieving this certification provides a clear signal to recruiters and hiring managers that you are prepared to handle the responsibilities of a modern data engineering role.

What the DEA-C01 Exam Covers

The DEA-C01 exam is structured around four primary domains that reflect the day-to-day responsibilities of a data engineer working in the cloud. Candidates must demonstrate proficiency in Data Ingestion and Transformation, which involves moving data from various sources into AWS and processing it for analysis using services like AWS Glue, Amazon Kinesis, and AWS Lambda. Data Store Management is another critical area, requiring knowledge of how to select and configure the right storage solutions, such as Amazon S3, Amazon RDS, or Amazon Redshift, to meet specific performance and cost requirements. Data Operations and Support focuses on the ongoing maintenance of these systems, including monitoring, logging, and automating workflows to ensure reliability. Finally, Data Security and Governance ensures that candidates understand how to protect data at rest and in transit, manage access controls, and comply with organizational policies. Our practice questions are designed to cover these domains comprehensively, allowing you to test your knowledge across the entire spectrum of the exam syllabus.

Among these domains, Data Operations and Support often presents the most significant challenge for candidates because it requires a shift in mindset from building systems to maintaining them under real-world conditions. This area tests your ability to troubleshoot pipeline failures, optimize performance, and implement automated recovery processes using tools like Amazon CloudWatch and AWS EventBridge. To succeed here, you must understand not just how to set up a service, but how to monitor its health and respond to incidents effectively. Candidates need to demonstrate a deep understanding of operational excellence, which includes implementing CI/CD pipelines for data infrastructure and managing the lifecycle of data assets. This requires a level of practical experience that goes beyond theoretical knowledge, making it essential to use high-quality practice questions to simulate the troubleshooting scenarios you will encounter on the actual exam.

Are These Real DEA-C01 Exam Questions?

It is important to clarify that our practice questions are sourced and verified by the community, consisting of IT professionals and recent test-takers who have sat for the actual exam. These individuals contribute their insights to ensure that our questions reflect what appears on the real exam, providing a realistic assessment of your readiness. We prioritize a community-verified approach because it ensures that the content remains relevant and accurate as the exam evolves. If you have been searching for DEA-C01 exam dumps or braindump files, our community-verified practice questions offer something more valuable, each question is verified and explained by IT professionals who recently passed the exam. This method provides a reliable way to gauge your knowledge without relying on unauthorized or leaked materials that often contain incorrect information.

The community verification process is what makes our platform a trusted resource for your exam preparation. When a question is added or updated, it undergoes a rigorous review where users discuss the answer choices, flag potentially incorrect information, and share context from their own recent exam experiences. This collaborative environment allows you to see different perspectives on how to approach complex scenarios, which is far more beneficial than simply memorizing answers. By engaging with these discussions, you gain a deeper understanding of the underlying concepts, which is the most effective way to prepare for the certification exam. This transparency and collective intelligence ensure that you are studying with high-quality, reliable material that truly helps you prepare for the challenges of the DEA-C01.

How to Prepare for the DEA-C01 Exam

Effective exam preparation requires a combination of hands-on experience and a thorough understanding of AWS documentation. You should spend significant time in a sandbox environment, building and breaking data pipelines to see how different services interact in practice. Do not rely solely on reading; you must actively configure services like Amazon Glue, S3, and Redshift to understand their limitations and best practices. Every practice question on our platform includes a free AI Tutor explanation that breaks down the reasoning behind the correct answer, so you understand the concept, not just the answer. This AI Tutor is designed to help you connect the dots between the theory you read in whitepapers and the practical application required to solve scenario-based questions on the exam.

A common mistake candidates make is attempting to memorize the answers to practice questions rather than understanding the logic behind them. The DEA-C01 exam is heavily scenario-based, meaning you will be presented with complex business problems that require you to apply your knowledge to find the most efficient or secure solution. To avoid this trap, use our practice questions to identify your weak areas and then return to the official AWS documentation to reinforce those specific topics. Additionally, time management is a critical skill; use your study sessions to practice answering questions under timed conditions to ensure you can maintain your pace during the actual exam. By focusing on conceptual understanding and consistent practice, you will build the confidence needed to pass the certification exam on your first attempt.

What to Expect on Exam Day

On the day of your exam, you should be prepared for a rigorous assessment that tests your ability to make architectural and operational decisions in a cloud environment. The exam format typically consists of multiple-choice and multiple-response questions, often presented as complex scenarios that require you to select the best solution based on criteria like cost, performance, security, or operational overhead. These exams are administered in a controlled environment, either at a physical testing center or via an online proctoring service like Pearson VUE. You will have a set amount of time to complete the exam, and it is crucial to manage your time effectively, as some questions may be more time-consuming than others. Familiarizing yourself with the interface and the types of questions beforehand will help reduce anxiety and allow you to focus entirely on the technical content.

Amazon certification exams are designed to be challenging, and you should expect to encounter questions that require you to synthesize information from multiple AWS services. There is no single "trick" to passing; success comes from a comprehensive understanding of the AWS Well-Architected Framework and how it applies to data engineering. You will likely face questions that ask you to choose between two technically viable solutions, where the correct answer depends on a specific constraint mentioned in the scenario. Pay close attention to keywords in the question stem, such as "most cost-effective," "least operational overhead," or "highest availability," as these are the keys to selecting the right answer. By preparing with a focus on these nuances, you will be well-equipped to handle the pressure and complexity of the actual testing environment.

Who Should Use These DEA-C01 Practice Questions

These practice questions are intended for data engineers, ETL developers, and cloud architects who are actively pursuing the AWS Certified Data Engineer - Associate certification. If you have at least one to two years of experience working with AWS data services and are looking to formalize your expertise, this resource is designed for you. The goal of this exam preparation is to bridge the gap between your daily work experience and the specific requirements of the certification exam. Whether you are looking to advance your career, validate your skills for a new role, or simply deepen your understanding of AWS data architecture, these questions provide the structured practice you need. By using these materials, you are taking a proactive step toward achieving a recognized Amazon certification that carries significant weight in the IT industry.

To get the most out of these practice questions, do not simply treat them as a quiz to be completed quickly. Instead, treat each question as a learning opportunity; if you get a question wrong, read the AI Tutor explanation carefully and review the community discussions to understand why your initial reasoning was incorrect. Flag the questions that you find particularly difficult and revisit them periodically to ensure that you have truly mastered the concept. Engaging with the material in this way will help you retain information longer and apply it more effectively in your professional work. Browse the questions above and use the community discussions and AI Tutor to build real exam confidence as you work toward your certification goal.

Amazon DEA-C01 Exam Actual Questions AWS Certified Data Engineer - Associate DEA-C01 (Page 2 )

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What the DEA-C01 Exam Tests and How to Pass It

What the DEA-C01 Exam Covers

Are These Real DEA-C01 Exam Questions?

How to Prepare for the DEA-C01 Exam

What to Expect on Exam Day

Who Should Use These DEA-C01 Practice Questions

Amazon DEA-C01 Exam Actual Questions
AWS Certified Data Engineer - Associate DEA-C01 (Page 2 )