DEA-C01 Data Ingestion and Transformation Practice Question
A data engineer is orchestrating a multi-step ingestion workflow where CSV files land in Amazon S3, an AWS Glue job transforms them, and the output is loaded into Amazon Redshift. The engineer wants conditional branching, retry logic, and the ability to pass parameters between steps. Which AWS service should be used to orchestrate this workflow?
⚠ Common exam trap
The trap here is assuming that Glue triggers or EventBridge rules provide full workflow orchestration, when they lack rich branching and retry semantics.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
AWS Step Functions with a state machine that invokes Glue and Redshift tasks.
Step Functions is a state-machine-based orchestrator that natively supports choice states for conditional branching, retry and catch blocks for fault tolerance, and input and output passing between states. It integrates with AWS Glue and Amazon Redshift, so the entire CSV-to-transformed-to-Redshift workflow can be modeled, monitored, and retried as a single managed execution with clear visibility into each step.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
AWS Glue workflows with triggers that chain crawlers and jobs together.
Why it's wrong here
Glue workflows and triggers can schedule and chain crawlers and jobs, but their conditional logic and error handling are limited compared with a general state machine. They do not offer rich branching or fine-grained retry semantics, and passing arbitrary parameters between heterogeneous steps is constrained. This makes them less capable of meeting all the stated orchestration requirements.
- ✗
Amazon EventBridge rules that react to S3 events and start the Glue job.
Why it's wrong here
EventBridge can route events and trigger targets, which is useful for event-driven initiation, but it is not a workflow engine with state, branching, and retry semantics across steps. It cannot natively sequence the Glue job and the Redshift load with conditional logic or carry parameters between them. This option covers triggering only, not full orchestration.
- ✓
AWS Step Functions with a state machine that invokes Glue and Redshift tasks.
Why this is correct
Step Functions supports conditional branching through choice states, configurable retry and catch logic, and passing data between states. It can invoke AWS Glue jobs and Amazon Redshift operations, making it suitable for orchestrating a multi-step ingestion workflow with the exact control-flow features described. This directly satisfies branching, retries, and parameter passing across the pipeline steps.
- ✗
AWS Lambda functions chained by direct invocations to run each pipeline step.
Why it's wrong here
Chaining Lambda functions by direct invocation creates custom orchestration code with no built-in state tracking, branching constructs, or standardized retry policies. Long-running Glue jobs and Redshift loads exceed typical Lambda execution patterns and complicate error handling. This approach reinvents orchestration logic that Step Functions provides natively, increasing maintenance and failure risk.
Quick reference
AWS S3 Storage Class Comparison
| Storage Class | Min Duration | Retrieval | Use Case |
|---|---|---|---|
| S3 Standard | None | Immediate | Frequently accessed data |
| S3 Standard-IA | 30 days | Immediate | Infrequent access, rapid retrieval |
| S3 One Zone-IA | 30 days | Immediate | Non-critical infrequent data |
| S3 Intelligent-Tiering | None | Immediate–hours | Unknown or changing access patterns |
| S3 Glacier Instant | 90 days | Milliseconds | Archive with instant retrieval |
| S3 Glacier Flexible | 90 days | Minutes–hours | Archive, flexible retrieval |
| S3 Glacier Deep Archive | 180 days | Hours | Long-term compliance archive |
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Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Amazon Web Services exam blueprint
This DEA-C01 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the DEA-C01 exam.