DEA-C01 Real Exam Questions
AWS Certified Data Engineer - Associate (DEA-C01) Exam. Everything you need to prepare, practice, and pass.
308
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4
Exam Domains
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Explanations
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Certification Overview
This exam tests your ability to ingest diverse data sources, transform and catalog that data using AWS Glue, optimize storage and query performance across Redshift and Athena, manage data operations at scale, and implement security controls for sensitive data—covering the full lifecycle of modern data engineering on AWS.
What This Certification Proves
The AWS Certified Data Engineer - Associate validates your ability to design, build, and maintain data pipelines and analytics solutions on AWS. This certification demonstrates proficiency in data ingestion, transformation, storage optimization, and security—essential skills for organizations modernizing their data infrastructure with AWS services.
Who Should Take This Exam
Data engineers with 1-2 years of hands-on experience using AWS services; professionals transitioning from other cloud platforms; analytics engineers looking to formalize AWS data engineering skills; anyone responsible for designing or operating ETL and data pipeline solutions on AWS.
Topic Breakdown
4 domains covering 308 questions
| Domain | Questions | Weight |
|---|---|---|
| Data Ingestion And Transformation | 138 | 45% |
| Data Store Management | 73 | 24% |
| Data Security And Governance | 56 | 18% |
| Data Operations And Support | 41 | 13% |
Study Plans
Choose a study plan that matches your schedule and experience level
30 Days
Intensive Sprint
Week 1-2
- Master fundamentals: Data Ingestion And Transformation
- Read Amazon official documentation
- Complete 11 questions daily
Week 3
- Deep dive: Data Store Management
- Review weak areas from results
- Take 2 full-length exams
Week 4
- Review all flagged questions
- Timed exams to build stamina
- Final revision of key concepts
60 Days
Balanced Approach
Week 1-2
- Survey all exam domains
- Set up study environment
- Begin with foundational topics
Week 3-4
- Focus: Data Ingestion And Transformation
- Focus: Data Store Management
- 6 questions daily
Week 5-6
- Focus: Data Security And Governance
- Hands-on labs if applicable
- Review explanations for wrong answers
Week 7-8
- Complete all 308 questions
- Identify and eliminate weak areas
- Take 3 full-length timed tests
90 Days
Comprehensive Study
Month 1
- Learn all exam domains at a comfortable pace
- Build strong foundational knowledge
- 4 questions daily
Month 2
- Deep dive into each domain
- Hands-on practice and labs
- Take weekly timed exams
Month 3
- Work through all 308 questions
- Identify and eliminate weak areas
- Take 3 full-length timed exams
DEA-C01-Specific Tips
- Focus heavily on AWS Glue hands-on labs—practice job creation, data catalog management, and ETL job debugging since it dominates the exam domains
- Run real cost optimization exercises with Redshift and Athena to understand when to use each service and how to optimize query performance and spending
- Build an end-to-end ETL pipeline using Glue + Athena or Glue + Redshift; the exam tests architectural decisions, not just individual service knowledge
- Deep dive into Glue Data Catalog—understand schema inference, versioning, and integration with other AWS services (this bridges multiple domains)
- Practice data security scenarios: Lake Formation permissions, encryption at rest/in transit, sensitive data masking, and compliance requirements like GDPR compliance in data pipelines
- Study Lambda for lightweight data transformation and orchestration—understand when it's better than Glue and cost implications
- Review AWS documentation on data governance and Athena query performance tuning; these topics have high representation in the domains listed
Relevant Career Roles
Sample Questions
Try 5 free questions from the DEA-C01 question bank
A data engineer is building a data pipeline. A large data file is uploaded to an Amazon S3 bucket once each day at unpredictable times. An AWS Glue workflow uses hundreds of workers to process the file and load the data into Amazon Redshift. The company wants to process the file as quickly as possible. Which solution will meet these requirements?
A company uses AWS Glue Apache Spark jobs to handle extract, transform, and load (ETL) workloads. The company has enabled logging and monitoring for all AWS Glue jobs. One of the AWS Glue jobs begins to fail. A data engineer investigates the error and wants to examine metrics for all individual stages within the job. How can the data engineer access the stage metrics?
A company uses Amazon S3 to store data and Amazon QuickSight to create visualizations, The company has an S3 bucket in an AWS account named Hub-Account. The S3 bucket is encrypted by an AWS Key Management Service (AWS KMS) key. The company's QuickSight instance is in a separate account named BI-Account. The company updates the S3 bucket policy to grant access to the QuickSight service role. The company wants to enable cross-account access to allow QuickSight to interact with the S3 bucket. Which combination of steps will meet this requirement? (Choose two.)
A company currently stores all of its data in Amazon S3 by using the S3 Standard storage class. A data engineer examined data access patterns to identify trends. During the first 6 months, most data files are accessed several times each day. Between 6 months and 2 years, most data files are accessed once or twice each month. After 2 years, data files are accessed only once or twice each year. The data engineer needs to use an S3 Lifecycle policy to develop new data storage rules. The new storage solution must continue to provide high availability. Which solution will meet these requirements in the MOST cost-effective way?
Which of the following best describes the type of data found in traditional relational databases?
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