DEA-C01 is about building and running data pipelines on AWS: getting data in, transforming it, storing it well, keeping it healthy and keeping it secure. This outline follows the four exam domains and the 17 task statements in the official exam guide, in plain terms. Tick topics off as you cover them. Your ticks are saved in this browser.
This outline follows the official DEA-C01 exam guide . Check it for the exact wording.
34%
Ingesting streaming and batch data, transforming it at scale, orchestrating pipelines and applying programming practice. The largest domain (34%).
Ingestion patterns and characteristics Reading from streaming sources Reading from batch sources and APIs Triggers, schedules and limits Transform and process data Building ETL pipelines from business requirements, intermediate staging in S3 Volume, velocity and variety, structured vs unstructured data Apache Spark and distributed computing concepts, skew and shuffles AWS Glue: jobs, DynamicFrames, bookmarks, pushdown predicates, worker types, Flex Amazon EMR on EC2, Serverless and EKS, Spot task nodes and transient clusters Lambda, Redshift and Managed Service for Apache Flink as transform engines Converting formats such as CSV to Parquet, ORC and Avro Connecting through JDBC and ODBC and integrating multiple sources Optimising container usage on ECS and EKS, and AWS Batch Optimising processing cost Troubleshooting transformation failures: memory, skew, small files, connectivity Creating data APIs with API Gateway and the Redshift Data API Orchestrate data pipelines Programming concepts
Data store management 26% Choosing and configuring stores, cataloguing data, managing its lifecycle and modelling it so it can evolve. 26% of the exam.
Choosing a data store Characteristics of S3, Redshift, DynamoDB, RDS/Aurora, EMR, Kinesis, MSK, OpenSearch, Neptune, DocumentDB, Keyspaces and MemoryDB Matching storage to access pattern, performance and cost Data formats: CSV, text, Parquet, ORC, Avro and open table formats such as Iceberg Provisioned vs serverless storage and analytics services Managing locks in Redshift and RDS Redshift design and access Migration and remote access Data cataloguing Lifecycle management Data modelling and schema evolution
Data operations and support 22% Automating, querying, monitoring and troubleshooting pipelines, and proving data quality. 22% of the exam.
Automating data processing Analysing data Athena: cost control, partitions, CTAS, views, workgroups and federated queries Athena notebooks with Apache Spark Provisioned vs serverless trade-offs SQL: joins, aggregation, grouping, pivoting and rolling averages Cleansing techniques with Lambda, Athena, DataBrew and notebooks Visualising with QuickSight, DataBrew and SageMaker Data Wrangler Monitoring and maintaining pipelines Data quality
Data security and governance 18% Authentication, authorization, encryption, audit logging and privacy for data pipelines. 18% of the exam.
Authentication VPC networking: security groups, subnets, gateway and interface endpoints, PrivateLink Managed vs unmanaged services and shared responsibility Password, certificate and role-based authentication AWS managed vs customer managed policies IAM groups, roles and trust policies for Lambda, API Gateway, CLI, CloudFormation, Glue, EMR and Redshift Credentials and rotation with Secrets Manager S3 Access Points and PrivateLink policies Authorization Role-based, policy-based, tag-based and attribute-based access Least privilege, custom IAM policies, policy evaluation and cross-account access Secrets Manager vs Systems Manager Parameter Store Database users, groups and roles in Redshift, plus row and column permissions Lake Formation permissions, LF-Tags, data filters, for Redshift, EMR, Athena and S3 Encryption and masking Encryption at rest for S3, Redshift, EMR, Glue, DynamoDB, RDS, Kinesis and MSK Client-side vs server-side encryption and SSE options KMS: key types, key policies, rotation, grants, multi-Region keys Encryption across account boundaries Encryption in transit with TLS Masking, anonymisation, hashing and key salting Audit logging Privacy and governance