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DEA-C01 Data Ingestion and Transformation Practice Question
Arrange the steps to create an AWS Glue job that transforms data from Amazon S3 to Amazon Redshift in the correct order.
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
✓
Step 1: Catalog the source data with a crawler. Step 2: Prepare the ETL script. Step 3: Configure the job with connections. Step 4: Run the job. Step 5: Verify the results in Amazon Redshift.
First, catalog the source data with a crawler. Then, prepare the ETL script. Configure the job with connections, run it, and finally verify the results in Redshift.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Step 1: Catalog the source data with a crawler. Step 2: Prepare the ETL script. Step 3: Configure the job with connections. Step 4: Run the job. Step 5: Verify the results in Amazon Redshift.
Why this is correct
This is the correct order because you first need to understand the data by cataloging it, then write the ETL script based on that schema, configure the job including connections, execute the job, and finally verify the output in Redshift.
- ✗
Step 1: Prepare the ETL script. Step 2: Catalog the source data with a crawler. Step 3: Configure the job with connections. Step 4: Run the job. Step 5: Verify the results in Amazon Redshift.
Why it's wrong here
This is incorrect because you cannot prepare an effective ETL script without first cataloging the source data to understand its schema and structure.
- ✗
Step 1: Configure the job with connections. Step 2: Catalog the source data with a crawler. Step 3: Prepare the ETL script. Step 4: Run the job. Step 5: Verify the results in Amazon Redshift.
Why it's wrong here
This is incorrect because cataloging should precede configuring connections; you need to know the source and target schemas before setting up connections.
- ✗
Step 1: Catalog the source data with a crawler. Step 2: Configure the job with connections. Step 3: Prepare the ETL script. Step 4: Run the job. Step 5: Verify the results in Amazon Redshift.
Why it's wrong here
This is incorrect because the ETL script should be prepared before configuring the job, as the script logic determines the necessary connections and job parameters.
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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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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.