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Keep shoppingAWS Certified Data Engineer Associate: DEA-C01 Practice Exam
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AWS Certified Data Engineer Associate: DEA-C01 Practice Exam
Master AWS Certified Data Engineer Associate (DEA-C01) exam with expert practice tests & detailed solutions | CertShield
Last updated 2/2026
English
What you'll learn
- Core Skills and Knowledge
- Data Ingestion and Transformation:
- - Designing efficient and scalable data collection solutions for various sources (e.g., real-time, batch).
- - Implementing ETL (Extract, Transform, Load) processes to prepare data for analytics.
- - Orchestrating data pipelines for reliability and scalability using AWS services.
- Storage and Data Management:
- - Selecting appropriate data storage services (S3, Redshift, DynamoDB, etc.) based on use case, performance, and cost considerations.
- - Optimizing data formats (Parquet, ORC, etc.) for analytics.
- - Managing data catalogs, schemas, and data lifecycle processes.
- Data Operations and Support:
- - Operationalizing data pipelines for production environments.
- - Maintaining and troubleshooting data processes to ensure reliability.
- - Monitoring data quality and implementing data validation checks.
- Data Security and Governance:
- - Implementing security best practices (encryption, authentication, authorization) across your data solutions.
- - Ensuring compliance with data privacy regulations.
- - Setting up logging and monitoring for auditing and security analysis.
- AWS-Specific Services: The exam heavily emphasizes the following AWS services:
- S3: Object storage, data lake concepts, lifecycle management.
- Athena: Interactive querying directly on data stored in S3.
- Glue: ETL, data catalog creation, and job scheduling.
- EMR: Managed big data frameworks (Spark, Hadoop, etc.) for processing.
- Kinesis: Real-time data streaming, analytics, and delivery (Data Streams, Data Firehose, Data Analytics).
- Redshift: Data warehousing for large-scale, structured data analysis.
- DynamoDB: NoSQL database for fast, flexible data models.
- RDS: Managed relational databases (MySQL, PostgreSQL, etc.).
- IAM: Identity and Access Management for controlling access to AWS resources.
- CloudWatch: Monitoring and logging for AWS infrastructure and services.
- Lake Formation: Centralized data lake management for permissions and governance.
Explore related topics
Included in This Course
215 questions
Description
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You are technically supported in your certification journey - please use Q&A for any query.
You are covered with 30-Day Money-Back Guarantee.
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Alignment with Real Exam: Questions mirror the content, difficulty level, and format of the actual exam you're preparing for. This lets you gauge your knowledge accurately and get familiar with the exam structure.
Comprehensive Coverage: The practice exam cover all major topics and concepts likely to appear on the real test.
Varying Difficulty Levels: Include questions with a mix of difficulty levels (easy, medium, hard) to simulate the real exam experience and identify your strengths and weaknesses.
Detailed Explanations: Every answer, correct or incorrect with clear, concise explanations. These help you understand why an answer is right/wrong, reinforcing your knowledge beyond simple memorization.
Why Consider the DEA-C01 Certification?
Validate Expertise: Earn an industry-recognized certification proving your proficiency in data engineering on AWS.
Career Advancement: Boost your credibility and open doors to new opportunities within the data engineering field.
Deepen Your AWS Skills: Solidify your knowledge of AWS data services and best practices, becoming a more efficient and effective data solutions architect on the platform.
Amazon AWS Certified Data Engineer - Associate (DEA-C01) certification:
Purpose
Validation: This certification validates your knowledge and skills in designing, building, securing, and operating data solutions on AWS.
Industry Recognition: AWS certifications are widely recognized, enhancing your credibility as a data engineer.
Target Audience
Ideal for: Data engineers, data analysts, or professionals with similar roles who have experience working with AWS data services.
Recommended Experience: AWS recommends 2-3 years of hands-on experience in data engineering, including at least 1-2 years of experience with AWS services.
Exam Details
Format: Multiple-choice and multiple-response questions.
Duration: 130 minutes
Cost: $150 USD (Practice Exam: $20 USD)
Languages: English, Japanese, Korean, Simplified Chinese
Pass Mark: Scaled score of 700 (out of 1000)
Domains and Weightings
Domain 1: Data Ingestion and Transformation (34%)
Design data collection strategies and pipelines
Implement ETL processes and orchestration
Domain 2: Storage and Data Management (26%)
Design data stores, choose data formats
Manage data catalogs, schemas, and lifecycles
Domain 3: Data Operations and Support (22%)
Operationalize and maintain data pipelines
Analyze data, ensure quality
Domain 4: Data Security and Governance (18%)
Implement authentication, authorization, encryption
Establish privacy compliance, logging
Key AWS Services Covered in the Practice Exam
S3
Athena
Glue
EMR
Kinesis (Data Streams, Data Firehose, Data Analytics)
Redshift
DynamoDB
RDS
IAM
CloudWatch
Lake Formation
Preparation Resources
AWS Exam Guide
AWS Training and Courses
Practice Exams
Online Communities and Forums: Connect with other exam takers for study groups and discussions.
Tips
Deep Hands-on Experience: This is more crucial than theoretical knowledge. Work on various AWS data projects.
Exam Guide Thoroughly: It outlines core exam areas to focus your studies.
Practice Exams: Use them to get familiar with question styles and identify weak points.
Who this course is for:
- Data Engineers: Professionals who design, build, secure, and maintain data analytics systems on AWS. This includes tasks like data ingestion, transformation, storage, and provisioning for analysis.
- Data Analysts with AWS Experience: Those who work extensively with data analytics on AWS and want to deepen their understanding of the platform's capabilities and best practices for data engineering tasks.
- Solutions Architects: Professionals involved in designing AWS-based solutions involving data pipelines and analytics may find this certification valuable to strengthen their data solutioning skills.
- Database Developers: Those working with both relational and NoSQL databases on AWS can benefit from learning how to integrate these databases effectively within larger data solutions.
- ETL Developers: Professionals focused on Extract, Transform, and Load processes will gain expertise in using AWS services for large-scale data transformations.