DEA-C01 Data Ingestion and Transformation Practice Question
A company ingests JSON data from an S3 bucket into a Glue ETL job. The data contains nested structures and arrays. The team wants to flatten the data into a tabular format for analysis in Athena. Which Glue transformation is appropriate?
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
✓
Relationalize
The Relationalize transformation is specifically designed to flatten nested JSON and arrays into a tabular format suitable for Athena. Option A (Map) applies a function to each record but does not flatten structures. Option C (Filter) selects rows based on a condition. Option D (DropNullFields) removes null fields but does not address nested structures.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Map
Why it's wrong here
Map applies a function to each record, not for flattening.
- ✓
Relationalize
Why this is correct
Relationalize transforms nested JSON into relational tables suitable for querying.
- ✗
Filter
Why it's wrong here
Filter selects records based on a condition, does not transform structure.
- ✗
DropNullFields
Why it's wrong here
DropNullFields removes fields with null values, does not flatten nested structures.
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 |
Go deeper
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Same concept, more angles
1 more way this is tested on DEA-C01
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. A data engineer needs to transform JSON data from an S3 bucket using AWS Glue. The JSON contains nested arrays and objects. Which Glue transform is best suited for flattening nested structures?
easy- A.Unnest
- B.ResolveChoice
- ✓ C.Relationalize
- D.Map
Why C: The Relationalize transform is specifically designed to flatten nested JSON structures (arrays and objects) into a set of related tables, making it ideal for this use case. It automatically handles complex nesting by creating separate DataFrames for each nested level and linking them via foreign keys, which is exactly what is needed when ingesting JSON with nested arrays and objects into a relational format.
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.