- Decoding the Code: What the Letters and Numbers Signal
- Which DEA-C01 This Is (and Which It Is Not)
- What the Credential Actually Certifies
- The Four Domains Behind the Name
- Exam Mechanics: Format, Fee, Timing, Scoring
- Who Looks for This Credential
- Versions, Validity, and Renewal
- Reading the Scope Carefully: Known Discrepancies
- Sequencing Your Preparation Around the Weights
- Frequently Asked Questions
- DEA-C01 is the exam code for AWS Certified Data Engineer - Associate, delivered by AWS through Pearson VUE.
- The exam has 65 questions (50 scored, 15 unscored), 130 minutes, and a USD 150 fee plus applicable taxes.
- Passing requires a scaled score of 720 on a 100-1,000 scale, which is not a 72% raw score.
- Domain 1, Data Ingestion and Transformation, carries 34% of scored content and deserves the most study time.
Decoding the Code: What the Letters and Numbers Signal
If you have landed here asking what DEA-C01 means, the short answer is this: DEA-C01 is the exam code for the AWS Certified Data Engineer - Associate certification. AWS uses a consistent naming pattern for its certification exams, and the code is a compact label that identifies one specific exam within that catalog.
The pattern is easy to read once you see it. "DEA" is shorthand for Data Engineer Associate, "C01" marks the first version line of the exam, and the whole string identifies the exam itself, distinct from the credential name that appears on your digital badge. Related pages on this site cover the same question from slightly different angles, including What Does DEA-C01 Stand For? and What Is DEA-C01?. This article goes a step further and explains what is actually behind the code: the scope, the format, the people it is aimed at, and how the exam is maintained over time.
Which DEA-C01 This Is (and Which It Is Not)
The acronym "DEA-C01" is short enough that it can be mistaken for labels used in unrelated fields. On this site, and throughout this article, it refers only to the AWS exam. The governing body is AWS, the testing provider is Pearson VUE, and every figure quoted below (fee, question count, timing, scaled score, domain weights) belongs to that one credential and nothing else.
What the Credential Actually Certifies
The certification validates knowledge of building and maintaining data pipelines on AWS. The exam guide frames this through four content domains containing 17 task statements and 120 numbered skills. In plain terms, you are expected to understand how to:
- ingest data from streaming and batch sources and handle throttling, replayability, and fan-in/fan-out patterns;
- transform and process data with services such as AWS Glue, Amazon EMR, AWS Lambda, and Amazon Redshift;
- orchestrate pipelines with Step Functions, Amazon MWAA, EventBridge, and Glue workflows;
- choose and manage data stores, catalogs, lifecycles, and schemas;
- operate, monitor, and troubleshoot pipelines and verify data quality;
- apply authentication, authorization, encryption, masking, auditing, and governance controls.
It is a knowledge-based certification exam. It does not measure hands-on competence directly, and a practice-test result is not evidence of workplace ability. For a deeper treatment of what the label covers as a credential, see the companion page DEA-C01 Certification.
The Four Domains Behind the Name
The weights below are the published percentages of scored content. For a longer breakdown, the DEA-C01 exam domains guide walks through each content area.
| Domain | Weight | Task statements |
|---|---|---|
| Domain 1: Data Ingestion and Transformation | 34% | 1.1 Perform data ingestion; 1.2 Transform and process data; 1.3 Orchestrate data pipelines; 1.4 Apply programming concepts |
| Domain 2: Data Store Management | 26% | 2.1 Choose a data store; 2.2 Understand data cataloging systems; 2.3 Manage the lifecycle of data; 2.4 Design data models and schema evolution |
| Domain 3: Data Operations and Support | 22% | 3.1 Automate data processing; 3.2 Analyze data; 3.3 Maintain and monitor data pipelines; 3.4 Ensure data quality |
| Domain 4: Data Security and Governance | 18% | 4.1 Authentication; 4.2 Authorization; 4.3 Encryption and masking; 4.4 Prepare logs for audit; 4.5 Data privacy and governance |
Domain 1: the heavyweight
Data Ingestion and Transformation (34%)
The largest domain covers moving data in, reshaping it, and keeping the movement reliable.
- Streaming sources: Kinesis, Amazon MSK, DynamoDB Streams, DMS; batch sources: S3, Glue, EMR, AppFlow, Lambda.
- Schedulers and triggers: EventBridge, Apache Airflow, S3 Event Notifications.
- Throttling and rate limits for DynamoDB, RDS, and Kinesis; stream fan-in and fan-out; replayability.
- Format conversion such as .csv to Apache Parquet, transformation debugging, and LLM integration in processing.
- Orchestration with Step Functions, MWAA, and Glue workflows, plus SNS and SQS for alerts.
- Programming concepts: Lambda concurrency, IaC with CloudFormation and CDK, SAM packaging, CI/CD.
Domain 2: where the stores meet the schema
Data Store Management (26%)
This domain tests whether you can match a workload to the right store and keep that store organized.
- Selecting among Redshift, EMR, Lake Formation, RDS, DynamoDB, Kinesis Data Streams, and MSK based on cost and performance.
- Newer topics: HNSW indexing in Aurora PostgreSQL, fast key/value access in MemoryDB, Apache Iceberg open table formats, and vector index types (HNSW, IVF).
- Cataloging with the Glue Data Catalog, crawlers, partition synchronization, and business catalogs in SageMaker Catalog.
- Lifecycle controls: S3 Lifecycle tiers and expiration, S3 versioning, DynamoDB TTL, Redshift load/unload.
Domains 3 and 4: running it and protecting it
Domain 3 (22%) covers automation, analysis with Athena and QuickSight, pipeline monitoring through CloudWatch Logs and CloudTrail, and data quality techniques such as DataBrew rules and handling data skew. Domain 4 (18%) covers IAM roles and policies, Secrets Manager, Lake Formation permissions, KMS encryption including cross-account scenarios, masking, CloudTrail Lake, Macie for PII, and data sovereignty requirements. Even at 18%, security questions appear across the whole exam, so do not treat the smallest domain as optional.
Exam Mechanics: Format, Fee, Timing, Scoring
The code also implies a specific test experience. Here is what the published information establishes:
| Item | DEA-C01 detail |
|---|---|
| Questions | 65 total: 50 scored, 15 unscored (unscored items are not identified) |
| Time | 130 minutes |
| Item types | Multiple-choice (one correct answer, three distractors) and multiple-response (two or more correct among five or more options) |
| Passing score | Scaled 720 on a 100-1,000 scale |
| Fee | USD 150, plus applicable taxes |
| Delivery | Pearson VUE test center or online proctoring |
| Languages | English, Japanese, Korean, Simplified Chinese |
A few points deserve emphasis. Scoring is compensatory across the exam, so you do not need to pass each domain separately. Unanswered items count as incorrect, and there is no penalty for guessing, so answer everything. The 720 is a scaled score; a practice test percentage cannot be converted into it, which is explained further in the DEA-C01 passing score guide. For pricing context including the 50% next-exam discount benefit available to holders of an active AWS Certification (a benefit, not a guaranteed price), see the DEA-C01 certification cost breakdown.
Who Looks for This Credential
The target candidate described in the exam guide has two to three years of experience in data engineering or data architecture and one to two years of hands-on AWS experience. That is guidance, not an admission rule: AWS requires no prior certification, degree, mandatory course, or specific number of work hours. The minimum candidate age is 13, with parent or guardian consent for ages 13 to 17. The DEA-C01 requirements page covers eligibility in more detail.
In practice, the credential tends to be relevant to people whose job titles involve:
- data engineering and analytics engineering on AWS-based platforms;
- ETL and pipeline development using Glue, EMR, Lambda, and Step Functions;
- data lake and warehouse administration involving S3, Lake Formation, Athena, and Redshift;
- cloud or database engineers moving into streaming and analytics roles.
The exam guide also lists what is explicitly out of scope for the job role: machine-learning model training and inference, programming-language-specific syntax, and drawing business conclusions from data. That boundary matters for interpretation. Skill 1.4.3 names languages such as Python, SQL, Scala, R, Java, Bash, and PowerShell, but the exam tests programming concepts rather than syntax. No verified salary premium or issuer pass rate is published for this credential, so treat headline earnings claims cautiously. The salary analysis, jobs overview, and ROI discussion evaluate the evidence qualitatively.
Versions, Validity, and Renewal
The current exam guide is DEA-C01 Exam Guide v1.1, published December 12, 2025, the latest revision listed in the retrieved revision record. No separate effective date was established, and none should be inferred from the publication date. Recheck the guide before you book.
The credential is valid for three years. Renewal options, per the AWS Recertification table, include passing the latest version of the DEA-C01 exam or passing AWS Certified Generative AI Developer - Professional. The renewed period runs from the date you complete the recertification action, not from the previous expiry date. The Data Engineer Associate row lists no CEU/CPE route and no Skill Builder maintenance option, so do not assume routes that apply to other certifications.
Reading the Scope Carefully: Known Discrepancies
Because the guide says its content and service lists are not exhaustive and are subject to change, a few published inconsistencies are worth knowing about rather than papering over:
- AWS SCT: The v1.1 revision record removes AWS Schema Conversion Tool from the in-scope service list, yet Skill 2.4.3 still names AWS SCT alongside DMS Schema Conversion. Both observations stand. Learn DMS Schema Conversion well and treat SCT-specific depth as uncertain until AWS clarifies.
- Quick vs. QuickSight: The service inventory says Amazon Quick, while skills 3.2.1 and 3.2.2 say QuickSight. Both labels appear in the official material; do not assume more than that.
- S3 Tables: Amazon S3 Tables is listed twice in the storage inventory. The duplicate is a listing artifact, not an extra objective or extra weight.
Key Takeaway
Use the service lists as orientation, not as a checklist that replaces the skills. A service appearing in scope does not mean it is tested deeply, and services on the out-of-scope list (for example AWS Amplify, AWS AppSync, AWS X-Ray, and Amazon Pinpoint) can safely be ignored.
Sequencing Your Preparation Around the Weights
One short, DEA-C01-specific way to apply the weights is to schedule the heaviest domain first and the dependent topics next. The timeline below is a sketch, not a prescription; adjust it to your background and revisit the full study guide for deeper planning.
Domain 1 foundations
- Streaming versus batch ingestion, throttling, replayability, fan-out.
- Glue, EMR, Lambda transformations and Parquet conversion.
- Orchestration with Step Functions, MWAA, and EventBridge.
Domain 2 stores and catalogs
- Redshift, DynamoDB, RDS, and Lake Formation access patterns.
- Glue Data Catalog, crawlers, partitions, Iceberg, vector index concepts.
- S3 Lifecycle, versioning, TTL, and schema evolution.
Domain 3 operations
- Athena queries, CloudWatch and CloudTrail monitoring, DataBrew quality rules.
- Troubleshooting Glue and EMR pipelines, data skew.
Domain 4 and review
- IAM least privilege, Secrets Manager, KMS, Lake Formation permissions, Macie.
- Timed mixed-domain practice and review of weak areas.
Domains 1 and 2 together account for 60% of scored content, so front-loading them is a sensible default. For extra reinforcement, a one-page cheat sheet helps with last-minute recall, and the difficulty guide can help you judge how much time you personally need. When you want realistic practice on the question styles described above, the DEA-C01 practice tests are built around the four published domains. These are independently authored knowledge-preparation materials, not actual exam questions and not affiliated with AWS, and no practice result guarantees a pass.
Frequently Asked Questions
DEA-C01 is the exam code for AWS Certified Data Engineer - Associate. It identifies the specific AWS exam that validates knowledge of ingesting, transforming, storing, operating, securing, and governing data on AWS. Related explainers include What Does DEA-C01 Mean? and What Is DEA-C01 Certification?.
Strictly, DEA-C01 is the exam code, while the credential you earn is called AWS Certified Data Engineer - Associate. In everyday conversation people use the code for both, which is why the two names are often interchanged.
The fee is USD 150, with applicable taxes under AWS testing policies. No member versus non-member price schedule is published for this credential. An active AWS Certification provides a 50% discount benefit toward a next exam, subject to AWS terms.
You need a minimum scaled score of 720 on a 100-1,000 scale. This is not a 72% raw-score threshold, and scoring is compensatory across the whole exam rather than requiring a pass in each domain.
No. AWS requires no prior certification, degree, or mandatory course. The recommendation of two to three years in data engineering and one to two years on AWS is guidance for target candidates, not an admission requirement.
In short, the meaning of DEA-C01 is simple, but the scope behind it is broad. Treat the code as a pointer to one specific AWS exam, confirm details against the official guide, and let the published domain weights shape where your preparation time goes.