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AWS · DEA-C01 · Intermediate

AWS Data Engineer - Associate (DEA-C01) — Practice Questions and Mock Exam

The AWS Certified Data Engineer – Associate validates the ability to design and implement data pipelines, manage data stores, and ensure data quality and governance on AWS.

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Official DEA-C01 exam: 720 out of 1000 points to pass.

Checked against AWS · September 2026 · Current exam version

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Data Store Management1 / 5

A data engineer needs to manage the lifecycle of data stored in Amazon S3 to optimize costs. Raw data should remain in S3 Standard for 30 days, then move to S3 Standard-IA for 90 days, and finally transition to S3 Glacier Deep Archive. Which AWS feature should the engineer configure?

AlexFull explanation from Alex

S3 Lifecycle policies automate object transitions between storage classes based on age. Rules define transitions: Standard → Standard-IA (30 days) → Glacier Flexible → Glacier Deep Archive, following the storage class waterfall. Minimum storage durations apply (30 days IA, 90 days Glacier, 180 days Deep Archive). Policies apply to buckets, prefixes, or tags with optional expiration rules. S3 Replication copies objects across buckets/regions but doesn't change storage classes over time. S3 Object Lock prevents deletion/modification for compliance (WORM), not cost optimization. S3 Intelligent-Tiering automatically moves objects between access tiers based on usage patterns but doesn't follow the fixed time-based schedule specified in this scenario. Ref: docs.aws.amazon.com/AmazonS3/latest/userguide/object-lifecycle-mgmt.html

Sourcedocs.aws.amazon.com

Data Operations and Support2 / 5

A data platform team needs to build a centralized observability dashboard that visualizes metrics from multiple AWS data services including AWS Glue, Amazon Redshift, Amazon EMR, and Amazon Kinesis. The dashboard must support custom alerting rules and integrate with PagerDuty for incident notification. Which AWS service provides these capabilities as a fully managed solution?

AlexFull explanation from Alex

Amazon Managed Grafana is a fully managed visualization service natively integrating with AWS data sources including CloudWatch, OpenSearch, X-Ray, Timestream, and Managed Prometheus. It enables centralized observability dashboards combining metrics from Glue, Redshift, EMR, Kinesis, and other services. Grafana supports custom alerting rules with contact points including PagerDuty, Slack, SNS, and email. It handles infrastructure, scaling, patching, and HA, with IAM Identity Center (SSO) for authentication. The option “Amazon CloudWatch Dashboards” (CloudWatch Dashboards) provides basic CloudWatch metric visualization but has limited customization, no native PagerDuty integration, and cannot natively combine non-CloudWatch sources. The option “AWS X-Ray service map” (X-Ray service map) focuses on distributed tracing, not general observability dashboards. The option “Amazon QuickSight” (QuickSight) is a BI service for data analytics and reporting, not operational monitoring or alerting.

Sourcedocs.aws.amazon.com

Data Security and Governance3 / 5

A data governance team manages a data lake with hundreds of databases and thousands of tables in the AWS Glue Data Catalog. They need to implement access control that scales efficiently without creating individual permissions for each table. When new tables are added to a database, they should automatically inherit the correct access permissions based on their data classification (e.g., 'PII', 'confidential', 'public'). Which AWS Lake Formation feature meets this requirement?

AlexFull explanation from Alex

Lake Formation tag-based access control (LF-TBAC) uses LF-Tags—key-value pairs like classification=PII—assigned to Data Catalog resources. Permissions are granted via tag expressions rather than individual resource grants. Tables inherit tags from databases and columns inherit from tables, so new tables automatically inherit permissions without manual grants. For N principals and R resources, named resource grants require N×R operations vs. N+R with LF-TBAC. IAM identity-based policies require per-table resource ARNs that don't scale for thousands of tables. Named resource grants require individual per-table permissions without inheritance. S3 bucket policies operate at the object/prefix level and don't understand table/column structure. Ref: docs.aws.amazon.com/lake-formation/latest/dg/tag-based-access-control.html

Sourcedocs.aws.amazon.com

Data Ingestion and Transformation4 / 5

A data engineer needs to orchestrate a multi-step data pipeline that includes an AWS Glue crawler, followed by an AWS Glue ETL job, and then a notification via Amazon SNS upon completion. The pipeline should run daily. Which combination of services provides the MOST operationally efficient solution?

AlexFull explanation from Alex

Use AWS Glue workflows when the dependency graph is made up of Glue crawlers and Glue jobs. A workflow start trigger can be scheduled daily, and conditional triggers can run later Glue steps after earlier steps complete. For notifications, AWS Glue emits EventBridge events for job and crawler state changes. An EventBridge rule can match the desired completion state and notify an Amazon SNS topic. Step Functions is valid for more heterogeneous orchestration, but it is not the lowest-overhead choice for a small Glue-native pipeline plus notification.

Sourcedocs.aws.amazon.com

Data Security and Governance5 / 5

A data engineer needs row-level AND column-level security for a data lake table in S3 queried by Athena. Different teams see different subsets of rows and columns. Which service provides BOTH in a centralized way?

AlexFull explanation from Alex

AWS Lake Formation data filters provide column-level, row-level, and cell-level security for Data Catalog tables stored in S3. Each data filter specifies: (1) a column specification to include/exclude columns, and (2) a row filter expression (PartiQL WHERE clause) restricting visible rows. When both are set, you get cell-level security. Permissions are enforced through Athena, Redshift Spectrum, and EMR. IAM policies with S3 prefix conditions operate at the object/prefix level, not row/column level. Glue Data Catalog resource policies control catalog-level access, not data-level filtering. Athena workgroup settings manage query execution and cost, not data security. Ref: docs.aws.amazon.com/lake-formation/latest/dg/data-filtering.html

Sourcedocs.aws.amazon.com

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What you practice for DEA-C01.

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Data ingestion and processingSee the guide for weighting114 QuestionsPass-IT questions

Build pipelines that collect data, transform it into usable formats and run reliably.

Ingest batch and streaming data from services or APIs, handling schedules, event triggers, rate limits and replay requirements.
Combine and transform data with suitable processing services, including format conversion, large language model integration and performance or cost troubleshooting.
Orchestrate resilient workflows with services such as Step Functions or AWS Glue, including serverless tasks, dependencies and notifications.
Apply programming and distributed-processing concepts, testing, version control and infrastructure as code to develop and deploy repeatable pipelines.

Official certification objectives

Data storage and modelsSee the guide for weighting88 QuestionsPass-IT questions

Choose where data lives and maintain the catalogs, schemas and lifecycle rules needed to use it.

Select and configure data stores for access, performance and cost, including migration, open table formats and vector indexes.
Build and maintain technical and business catalogs, using schema discovery, crawlers and partition updates to keep data discoverable.
Manage transfers, storage tiers, retention, versioning and deletion while preserving required availability and resilience.
Design and evolve schemas, track data lineage and choose indexing, partitioning and compression strategies, including considerations for vector data.

Official certification objectives

Operating data pipelinesSee the guide for weighting73 QuestionsPass-IT questions

Keep processing dependable and make data suitable for analysis through monitoring and quality checks.

Automate processing and scheduling with AWS workflows, service APIs and event-driven functions, and troubleshoot managed workflows.
Query, explore, clean and visualize data with SQL and AWS analytics tools, understanding aggregation and serverless-service tradeoffs.
Maintain pipelines using logs, metrics and alerts to investigate failures and performance issues and preserve traceability.
Apply data-quality rules, sampling and consistency checks, and recognize or address uneven data distribution.

Official certification objectives

Data security and governanceSee the guide for weighting56 QuestionsPass-IT questions

Control data access, protect sensitive information and produce evidence for audits and governance.

Configure identities, service roles and secure credentials so users and pipeline components can authenticate appropriately.
Apply least-privilege permissions with IAM, database controls and Lake Formation, choosing role-, tag- or attribute-based access as needed.
Encrypt and mask sensitive data, managing keys and encryption across transfers and account boundaries.
Collect and analyze application and API activity logs, using services such as CloudTrail and CloudWatch to support audits.
Apply privacy, sharing and data-residency controls, identify personal information and track configuration changes affecting governance.

Official certification objectives

Question formats you can practice

Multiple Choice: Select one answer.
Multiple Response: Select multiple applicable answers.

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Frequently asked questions

Your preparation

How much study time should I plan for DEA-C01?

For planning, Pass-IT estimates roughly 30–75 hours. Relevant experience may put you toward the lower end; starting from scratch may put you toward the higher end. Your needs may fall outside this range. This is not a time requirement from AWS or a promise that you will be exam-ready within that time.

Do you need CLF-C02 before DEA-C01?

No, AWS sets no formal prerequisite for DEA-C01. The catalog budget is around 50 hours and assumes working knowledge of SQL and of AWS storage services. Cloud Practitioner helps if AWS itself is new to you, but it teaches nothing about pipelines.

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Questions in the app are currently in English. Translations of the sample questions on this page apply only to this preview. Check with AWS for the languages available for the official exam.

How long does my DEA-C01 access last?

Access covers this certification for 12 months. You pay once, with no automatic renewal.

When does the money-back guarantee apply?

The guarantee refunds the Pass-IT purchase price for this certification. You need eligible paid access and a Readiness Score of at least 80% from your practice results when you take the exam. This score can only reach 80% after at least 50 answered questions and is not a validated probability of passing. Take the exam during your access period and submit official proof of failing within 14 days. Guarantee terms

About the DEA-C01 exam

Where can I take the DEA-C01 exam?

Pearson VUE testing center or online proctored exam.

How long is the AWS Certified Data Engineer - Associate exam?

The DEA-C01 exam has 65 questions and a 130-minute time limit.

Which AWS certification fits a data engineer?

DEA-C01 is designed for the role: Data Ingestion and Transformation accounts for 34% of scored content, and Data Store Management for 26%. AWS Certified Machine Learning Engineer - Associate is the neighbouring associate-level certification for pipelines that end in model training. SAA-C03 focuses on general solution architecture. Choose DEA-C01 if your work centres on data pipelines, or the machine learning engineer certification if you focus on features and models.

How long is DEA-C01 valid?

The certification is valid for three years. You can renew it for three more years by passing the latest version of the exam or the AWS Certified Generative AI Developer - Professional exam. While your certification is active, you can also maintain it on AWS Skill Builder to extend it by one year.

What happens if you fail DEA-C01?

AWS makes you wait 14 days before the next attempt. There is no cap on how many times you can sit it, so the only hard limit is that two-week gap.

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The guarantee refunds the Pass-IT purchase price for this certification. You need eligible paid access and a Readiness Score of at least 80% from your practice results when you take the exam. This score can only reach 80% after at least 50 answered questions and is not a validated probability of passing. Take the exam during your access period and submit official proof of failing within 14 days.

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