DEA-C01 Exam Guide: AWS Data Engineer Associate Plan
Direct answer: DEA-C01 is the AWS Certified Data Engineer - Associate exam. It has 65 questions in 130 minutes, a passing score of 720 out of 1000, and four domains led by ingestion and transformation at 34%. Our voucher costs $48.99 and covers one attempt; if you have some AWS experience, plan for about 8 weeks at 6 to 8 hours a week.
What DEA-C01 proves and who should take it
DEA-C01 is the exam for the AWS Certified Data Engineer - Associate certification. It shows you can build and run data pipelines on AWS. That means ingesting data, transforming it, storing it well, and keeping it secure and reliable.
It suits data engineers, analytics engineers, ETL developers and cloud engineers who are moving into data work. AWS recommends real hands-on time with its data services. There is no formal prerequisite certification, so you can book it without holding another AWS exam first.
If you have never touched AWS, start with a fundamentals exam or a few weeks of labs. This exam assumes you already know what S3, IAM and a VPC are.
Exam format at a glance
These are the facts most candidates need before booking. AWS can change exam details, so confirm them in the official exam guide on the AWS Certification site before you pay.
Item | Detail |
|---|---|
Exam code | DEA-C01 |
Level | Associate |
Questions | 65 |
Time limit | 130 minutes |
Question types | Multiple choice, multiple response, ordering, matching |
Passing score | 720 on a scale of 100 to 1000 |
Scoring note | Some questions are unscored trial items; you cannot tell which |
Prerequisites | None required; hands-on AWS data experience recommended |
The score is scaled, so 720 is not a fixed percentage of correct answers. Do not try to calculate how many you can miss. Answer every question, because unanswered ones count as wrong.
Skills measured and domain weights
The exam has four domains. The weights below tell you where to spend your hours.
Domain | Weight |
|---|---|
1. Data Ingestion and Transformation | 34% |
2. Data Store Management | 26% |
3. Data Operations and Support | 22% |
4. Data Security and Governance | 18% |
Domain 1 alone is about a third of the exam. Expect many questions on AWS Glue, Kinesis, Amazon MSK, AWS Lambda and Step Functions. Domain 2 centers on S3, Redshift, DynamoDB and the Glue Data Catalog.
Domain 3 covers monitoring, data quality and pipeline troubleshooting. Domain 4 covers IAM, encryption with AWS KMS, Lake Formation and auditing. Security is the smallest domain, but it shows up inside questions from every other domain.
Cost: list price, our voucher price and refund terms
Our DEA-C01 voucher costs $48.99 USD as listed on the DEA-C01 voucher page. One voucher covers one exam attempt. Check the current AWS list price on the AWS Certification site so you can compare it with ours on the day you buy.
Here is how our delivery and refund terms work:
The voucher code is emailed within 12 hours of payment. You can also find your code in your account.
You can cancel an order for a full refund before delivery.
A delivered code is non-refundable, with one exception. If the test provider rejects it as invalid, already used or expired on first use, contact support within 14 days.
Send the order number and a screenshot. We will replace the code or refund you.
Look at any expiry date shown with your code, and book your exam slot before it passes.
An 8-week study plan
This plan assumes you already work with AWS or SQL a little. Plan on 6 to 8 hours per week, about 50 to 65 hours in total. If you are new to AWS, stretch it to 12 weeks.
Week | Focus | Hours |
|---|---|---|
1 | Read the official exam guide. Review S3, IAM, VPC basics. Build a small S3 data lake. | 6 |
2 | Glue crawlers, Data Catalog, ETL jobs. Athena queries and partitioning. | 8 |
3 | Streaming: Kinesis Data Streams, Firehose, MSK. Lambda triggers. | 8 |
4 | Orchestration: Step Functions, MWAA, EventBridge. Batch versus stream decisions. | 7 |
5 | Stores: Redshift, DynamoDB, RDS, formats such as Parquet. Lifecycle and cost. | 8 |
6 | Operations: CloudWatch, CloudTrail, Glue data quality, troubleshooting failed jobs. | 7 |
7 | Security: KMS, Lake Formation, IAM policies, masking, cross-account access. | 7 |
8 | Two timed practice sets of 65 questions. Review every miss. Light revision only in the last two days. | 8 |
Split each week roughly 40% reading or video and 60% hands-on labs. Labs are what make the scenario questions feel familiar.
A worked example to practice
A typical exam scenario: raw CSV files land in S3 each day, analysts run slow, costly Athena queries, and the team wants lower cost with minimal code. The usual answer is to convert to Parquet, partition by date, and query only the partitions needed.
Try it yourself in Athena:
CREATE TABLE sales_parquet
WITH (
format = 'PARQUET',
external_location = 's3://your-lab-bucket/curated/sales/',
partitioned_by = ARRAY['sale_date']
)
AS SELECT order_id, amount, sale_date
FROM sales_raw;The partition column must come last in the SELECT list. Run the same query on both tables and compare the "data scanned" figure. That number is the reason columnar formats and partitions appear so often on the exam.
Quick decision table
Exam questions often ask you to pick between similar services. Practice these pairs:
If the question stresses | Think first about |
|---|---|
Serverless ETL with a catalog | AWS Glue |
Near-real-time delivery to S3 or Redshift, little code | Kinesis Data Firehose |
Ordered, replayable streams with custom consumers | Kinesis Data Streams or MSK |
Ad hoc SQL directly on S3 | Athena |
Fast, repeated analytics on large structured data | Redshift |
Column-level or row-level access control on a lake | Lake Formation |
Treat this as a starting point, not a rule. The wording of each question decides the answer.
Common mistakes to avoid
Studying services in isolation. Questions describe a pipeline and ask for the best fix. Learn how services connect.
Skipping hands-on labs. Reading about Glue job bookmarks is not the same as watching one skip old files.
Ignoring cost and operations words. "Least operational overhead" and "most cost-effective" often decide between two valid answers.
Treating security as a side topic. KMS keys, bucket policies and Lake Formation permissions appear in many pipeline questions.
Memorizing leaked questions. Dumps break exam rules, can be wrong, and teach you nothing for the job. Use official practice questions and your own labs.
Running out of time. You have about two minutes per question. Flag long case-style questions and return to them.
After you pass
You receive a digital badge you can add to your resume and LinkedIn. AWS certifications are valid for a limited period, so check the recertification rules on the AWS Certification site and note your expiry date.
Natural next steps depend on your goal. If you are moving toward ML pipelines, look at the MLA-C01 voucher. For more options, browse our Data & Analytics certifications.
When you are ready to book, you can buy the DEA-C01 voucher and get the code by email within 12 hours.
Sources
Questions about this topic
Do I need to know Python and SQL for DEA-C01?
You will not write long programs in the exam, but you should read short SQL and Python snippets comfortably. SQL matters for Athena and Redshift questions. Basic Python helps you follow Glue and Lambda examples.
Can I take the exam online or only at a test center?
AWS has commonly offered both a test center and an online proctored option. Availability can vary by country, so check the options when you schedule. If you test online, run the system check and clear your desk first.
What happens if I fail my first attempt?
You will need a new voucher or payment for another attempt, because one voucher covers one attempt. AWS sets a waiting period before a retake, so read the current rule on its site. Use your score report to see which domains to strengthen.
Should I take DEA-C01 or MLA-C01 first?
Pick DEA-C01 if your daily work is pipelines, storage and analytics. Pick MLA-C01 if you build and deploy machine learning models. Many people find data engineering skills a useful base for ML work, but it is not required.
Is hands-on AWS experience really necessary?
AWS recommends it, and the scenario questions reward it. You can offset a lack of job experience with structured labs on the free tier or a small budget. Set billing alerts and delete resources after each lab.