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Exam Information
Official specifications published by Amazon
Exam Format
130 min
65
720
Associate
Registration
$150 USD
Pearson VUE, PSI, or online proctoring
Validity
3 years
Pass any AWS Professional-level exam; Pass any AWS Specialty exam; Pass the recertification exam for DEA-C01
DEA-C01 Exam Topics and Domains
DEA-C01 is organized into 4 weighted domains. Expect to work with AWS Lambda, AWS Glue, Amazon Redshift, Amazon S3, and more.
1
Data Ingestion and Transformation
34%
Perform data ingestion
Streaming Data IngestionBatch Data IngestionData Pipeline Scheduling
- Design and implement streaming data ingestion solutions using Kinesis and MSK
- Configure batch data ingestion using S3, Glue, and EMR
- Set up data pipeline scheduling with EventBridge and MWAA
- Handle throttling, rate limits, and data replay scenarios
- Optimize ingestion for cost and performance
Transform and process data
ETL/ELT Pipeline DesignData Format ConversionDistributed Processing
- Design ETL and ELT pipelines based on business requirements
- Transform data between different formats efficiently
- Implement distributed processing using EMR and Spark
- Optimize transformation costs and performance
- Handle transformation errors and data quality issues
Orchestrate data pipelines
Workflow OrchestrationServerless Workflows
- Design and implement orchestrated data pipelines
- Use MWAA and Step Functions for workflow management
- Build serverless data processing workflows
- Implement notification and monitoring systems
- Ensure pipeline reliability and scalability
Apply programming concepts
Infrastructure as CodeSQL and Query Optimization
- Implement Infrastructure as Code for data pipelines
- Write optimized SQL queries for data transformations
- Use AWS SAM for serverless deployments
- Configure Lambda functions for optimal performance
- Apply CI/CD practices to data engineering
2
Data Store Management
26%
Choose a data store
Data Store SelectionData Migration StrategiesStorage Optimization
- Select appropriate data stores based on requirements
- Plan and execute data migrations
- Optimize storage for performance and cost
- Implement partitioning and indexing strategies
- Design hybrid storage solutions
Understand data cataloging systems
Data Catalog ManagementMetadata and Schema Management
- Implement and manage data catalogs
- Use Glue crawlers for schema discovery
- Manage metadata and schema evolution
- Implement data classification systems
- Track data lineage across pipelines
Manage the lifecycle of data
Data Lifecycle PoliciesData Archival and Deletion
- Design data lifecycle management strategies
- Implement S3 Lifecycle policies
- Manage hot and cold data storage
- Ensure compliance with retention policies
- Optimize storage costs through lifecycle management
Design data models and schema evolution
Data Modeling ConceptsSchema Evolution and Lineage
- Design effective data models for different use cases
- Implement schema evolution strategies
- Track data lineage across systems
- Optimize models for performance
- Handle structured and unstructured data modeling
3
Data Operations and Support
22%
Automate data processing by using AWS services
Pipeline AutomationScripting and SDK Integration
- Automate data processing workflows
- Implement event-driven architectures
- Use AWS SDKs for custom automation
- Build resilient and self-healing pipelines
- Monitor and troubleshoot automated processes
Analyze data by using AWS services
Data Analysis and VisualizationData Quality and Cleansing
- Perform interactive data analysis
- Create visualizations and dashboards
- Implement data quality frameworks
- Clean and validate data
- Use serverless and managed analytics services
Maintain and monitor data pipelines
Pipeline MonitoringTroubleshooting and Optimization
- Implement comprehensive monitoring solutions
- Troubleshoot data pipeline issues
- Optimize pipeline performance
- Set up alerting and notifications
- Maintain pipeline reliability
Ensure data quality
Data Quality FrameworkData Consistency and Integrity
- Design data quality frameworks
- Implement automated quality checks
- Ensure data consistency and integrity
- Monitor quality metrics
- Remediate data quality issues
4
Data Security and Governance
18%
Apply authentication mechanisms
Identity and Access ManagementNetwork Security
- Implement IAM best practices
- Configure network security
- Manage credentials securely
- Set up cross-account access
- Implement principle of least privilege
Apply authorization mechanisms
Fine-grained Access ControlSecrets Management
- Implement fine-grained access controls
- Manage secrets and credentials
- Use Lake Formation for data permissions
- Apply tag-based access control
- Secure database access
Ensure data encryption and masking
Encryption StrategiesData Masking and Anonymization
- Implement encryption at rest and in transit
- Manage encryption keys with KMS
- Apply data masking techniques
- Protect PII and sensitive data
- Implement anonymization strategies
Prepare logs for audit
Audit LoggingCompliance and Monitoring
- Implement comprehensive audit logging
- Use CloudTrail for API tracking
- Aggregate and analyze logs
- Ensure compliance requirements
- Monitor security events
Understand data privacy and governance
Data Privacy RegulationsData Governance Framework
- Implement data privacy controls
- Ensure regulatory compliance
- Manage data governance policies
- Protect PII and sensitive data
- Implement data sovereignty requirements
How do I earn this certification?
Passing DEA-C01 earns the AWS Certified Data Engineer - Associate certification. It sits in the Data Engineering track.
Current Level Exams
Next Level Options
Alternative Paths
- MLA-C01 - AWS Certified Machine Learning Engineer - AssociateNatural progression for data engineers into ML
- AIF-C01 - AWS Certified AI PractitionerFoundation for AI/ML implementations
- PAS-C01 - AWS Certified SAP on AWS - Specialty Enterprise data integration skills
Practice with Precision
The PlanetCert Simulator mirrors the real exam environment with authentic questions and timed pressure.
How to study for this exam?
The most effective way to prepare for DEA-C01 is by using the PlanetCert Simulator to practice questions and review detailed explanations.
What's changed on this exam?
Current Status
- ACTIVE
- Last content update: 2024-03-12
- Announcement date: 2023-11-27
Updates
- Apache Iceberg
- Apache Hudi
- Delta Lake
Who should take this exam?
- 2-3 years of experience in data engineering
- 1-2 years of hands-on experience with AWS services
- Experience with data pipeline design and implementation
- Understanding of basic programming concepts
- Knowledge of SQL and data modeling