Updated 1 Nov 2026 · 6 min read
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What the AWS DEA-C01 is and who it is for
The DEA-C01 is the exam behind the AWS Certified Data Engineer Associate certification. AWS says it validates your ability to implement data pipelines and to monitor, troubleshoot, and optimise cost and performance issues in line with best practices. Around that core it tests four kinds of work: ingesting, transforming and orchestrating data, choosing data stores and managing data models and lifecycles, running and monitoring pipelines while keeping data quality high, and securing and governing the data.
AWS describes the target candidate as someone with the equivalent of two to three years of experience in data engineering and at least one to two years of hands-on experience with AWS services. There is no formal prerequisite, but AWS recommends that you know how to set up and maintain ETL pipelines, run SQL queries, use Git for source control and use data lakes to store data. AWS also lists what is out of scope: training machine learning models, language-specific programming syntax and drawing business conclusions from data.
The exam guide was revised to version 1.1 on 12 December 2025. In that revision AWS added skills on large language models for data processing, open table formats such as Apache Iceberg, vector index types, Amazon SageMaker Catalog and SageMaker Unified Studio. Older study material may not cover these.
AWS DEA-C01 at a glance
| Item | Detail |
|---|---|
| Exam code | DEA-C01 |
| Questions | 65, multiple choice or multiple response. 50 are scored and 15 are unscored and not identified |
| Time allowed | 130 minutes |
| Passing score | 720 on a scaled score of 100 to 1,000 |
| Exam fee | US$150, with prices in other currencies on the AWS exam pricing page |
| Languages | English, Japanese, Korean and Simplified Chinese |
| Where you sit it | Pearson VUE test centre or online proctored |
| Certification valid for | 3 years, renewed by passing the latest version of the exam |
What is on the exam
Data Ingestion and Transformation (34%). It carries the most weight. You read data from streaming sources such as Amazon Kinesis, Amazon MSK and DynamoDB Streams, and from batch sources such as Amazon S3, AWS Glue and Amazon EMR. You set up schedulers and event triggers with Amazon EventBridge, handle throttling and rate limits, and transform data between formats, for example from CSV to Apache Parquet. Orchestration with Amazon MWAA, AWS Step Functions and Glue workflows is here, along with programming concepts: Lambda concurrency, infrastructure as code with CloudFormation, the CDK and AWS SAM, CI/CD for pipelines, and using large language models to process data.
Data Store Management (26%). Choosing the right store for a cost, performance or access pattern: Amazon Redshift, Amazon RDS, DynamoDB, Lake Formation, Aurora PostgreSQL with vector indexing, and Amazon MemoryDB. You work with the AWS Glue Data Catalog and crawlers, partitions, business catalogs in SageMaker Catalog, S3 Lifecycle policies, S3 versioning and DynamoDB TTL. Schema design, schema conversion, data lineage, open table formats and vector concepts round it off.
Data Operations and Support (22%). Automating processing with Lambda, EventBridge, MWAA and Step Functions, querying with Amazon Athena and SQL in Redshift, and preparing data with Glue DataBrew and SageMaker Unified Studio. You monitor pipelines with Amazon CloudWatch Logs and AWS CloudTrail, troubleshoot Glue and EMR jobs, and run data quality checks with rules defined in DataBrew. Knowing when serverless beats provisioned capacity also sits here.
Data Security and Governance (18%). IAM roles and custom policies built on least privilege, VPC security groups, credentials in AWS Secrets Manager and Parameter Store, and permissions through AWS Lake Formation. Encryption with AWS KMS, including across accounts, data masking, PII discovery with Amazon Macie, audit logging with CloudTrail Lake, AWS Config, data sovereignty and SageMaker Unified Studio domains and projects complete the list.
Why people fail it
The DEA-C01 rarely asks what a service does. It asks which of several workable services fits a stated requirement, such as lowest cost, least operational overhead, near real time delivery or cross-account access. Glue against EMR, Kinesis Data Streams against Kinesis Data Firehose, Athena against Redshift Spectrum, Step Functions against MWAA: each pair can solve the problem, and the wording decides which one is right. Candidates who learn services one by one, rather than in comparison, lose marks here.
The second cause is the security and governance domain. It is only 18% of the exam, but Lake Formation permissions, KMS key policies across accounts and least-privilege IAM are detailed topics that many data engineers leave to someone else. Weak answers there are hard to make up elsewhere.
The third is time. 65 questions in 130 minutes leaves two minutes each, and many questions are long scenarios with similar options. Multiple response questions need every correct option, so reading carefully matters more than speed.
A study plan that fits the exam
Seven weeks suits most people who already work with AWS data services. The split follows the weights: two and a half weeks on ingestion and transformation, a week and a half on data stores, a week on operations, a week on security and a final week of timed practice.
- Week 1: ingestion. Streaming with Kinesis, MSK and DynamoDB Streams, batch loads with Glue, DMS and AppFlow, schedulers, event triggers and rate limits. End the week with the free DEA-C01 practice questions to find your gaps.
- Week 2: transformation and orchestration. Glue against EMR against Lambda, format conversion to Parquet, joining sources over JDBC, then Step Functions, MWAA and Glue workflows with SNS and SQS alerts.
- Week 3: programming concepts, then data stores. Lambda concurrency, CloudFormation, the CDK and SAM, CI/CD and LLM-based processing. Then start choosing stores: Redshift, RDS, DynamoDB and Aurora with vector indexing.
- Week 4: catalogs and lifecycle. Glue Data Catalog, crawlers and partitions, SageMaker Catalog, S3 Lifecycle, versioning, DynamoDB TTL, Iceberg tables, schema evolution and lineage.
- Week 5: operations and data quality. Athena and Redshift SQL, DataBrew, CloudWatch Logs, CloudTrail, troubleshooting Glue and EMR jobs, and data quality rules.
- Week 6: security and governance. IAM policies, Secrets Manager, Lake Formation permissions, KMS across accounts, Macie, AWS Config and SageMaker Unified Studio domains and projects.
- Week 7: timed runs. Work through the questions-only copy in the DEA-C01 practice question pack in 130 minute blocks and read the explanation for every miss, especially where two services looked right. AWS also offers an Official Practice Question Set and an Official Practice Exam on AWS Skill Builder.
On exam day
You sit the exam with Pearson VUE, at a test centre or online. At a test centre you need two forms of ID, and AWS asks you to arrive 15 to 30 minutes early. Online you need one primary ID and go through a self check-in before a proctor starts the exam.
There are no scheduled breaks. At a test centre you may take an unscheduled break, but the timer keeps running. Online you may not leave the camera view for any reason, so prepare before you start. The exam uses short names for some AWS services, and a list of full names is available through the Help button.
There is no penalty for a wrong answer and unanswered questions count as wrong, so answer every question. If English is not your first language and you sit in English, you can request a 30 minute extension, ESL +30. You request it once, before you register, and it then applies to all your future exam registrations. Results reach your AWS Certification Account within five business days.
Frequently asked questions
What happens if I fail the DEA-C01?
You must wait 14 calendar days before you can retake it. AWS sets no limit on attempts, but you pay the full fee each time. Your score report may show how you did in each section, which helps you plan the next attempt. Because scoring is compensatory, you need to pass the exam overall, not each domain.
How long does the certification last?
Three years. Before it expires, you recertify by passing the latest version of the exam.
Is the practice pack enough on its own?
No. It is practice, not a course. The 366 questions show how AWS frames service choices and explain why the wrong options are wrong, but the exam expects hands-on experience. Build a small pipeline yourself with Glue, Athena and Lake Formation, then use the questions to test yourself under time.
When you are ready to test yourself properly, get the DEA-C01 practice questions with full explanations.
Sources
The official pages the facts in this guide were checked against.
- docs.aws.amazon.com/aws-certification/latest/data-engineer-associate-01/data-engineer-associate-01.html
- docs.aws.amazon.com/aws-certification/latest/data-engineer-associate-01/dea-01-revisions.html
- aws.amazon.com/certification/certified-data-engineer-associate/
- docs.aws.amazon.com/aws-certification/latest/data-engineer-associate-01/data-engineer-associate-01-domain1.html
- docs.aws.amazon.com/aws-certification/latest/data-engineer-associate-01/data-engineer-associate-01-domain2.html
- docs.aws.amazon.com/aws-certification/latest/data-engineer-associate-01/data-engineer-associate-01-domain3.html
- docs.aws.amazon.com/aws-certification/latest/data-engineer-associate-01/data-engineer-associate-01-domain4.html
- docs.aws.amazon.com/aws-certification/latest/data-engineer-associate-01/dea-01-in-scope-services.html
- aws.amazon.com/certification/policies/during-testing/
- aws.amazon.com/certification/policies/before-testing/
- aws.amazon.com/certification/policies/after-testing/