DEA-C01 Data Ingestion and Transformation Practice Question
A data engineer needs to run a transformation in AWS Glue where each record must be processed independently and the output schema is known ahead of time. The transformation should operate on a DynamicFrame and return a DynamicFrame. Which Glue transform is designed for this row-by-row operation?
⚠ Common exam trap
Candidates often confuse schema-normalization transforms such as ResolveChoice or DropNullFields with the Map transform, which is the only one that applies custom per-record logic.
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
✓
Map
The Map transform is purpose-built for applying a function to each record and returning a DynamicFrame, which matches the need for independent row processing with a known output schema. Relationalize, ResolveChoice, and DropNullFields are schema or structure utilities, not general row-level mapping transforms.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
DropNullFields
Why it's wrong here
DropNullFields removes columns that are entirely null from a DynamicFrame. It is a schema-cleanup utility, not a record-level transformation, and it cannot apply custom business logic. Because it only eliminates empty columns and does not process individual rows, it does not meet the stated requirement.
- ✗
Relationalize
Why it's wrong here
Relationalize flattens nested structures into multiple relational tables, which is useful for loading semi-structured data into a relational database. It does not apply a user-defined function to each record, and it changes the schema by producing multiple frames. It is not a row-by-row mapping transform, so it does not fit this requirement.
- ✓
Map
Why this is correct
The Map transform applies a user-supplied function to every record in a DynamicFrame and returns a new DynamicFrame with the transformed records. It preserves the one-to-one record relationship, making it ideal when each record is processed independently and the output schema is predetermined. It is the canonical Glue transform for this pattern.
- ✗
ResolveChoice
Why it's wrong here
ResolveChoice handles columns that contain multiple data types by casting or separating them. It does not execute custom logic per record and does not let the engineer define output fields. While it can normalize schema, it is not a general-purpose row transformation, so it cannot satisfy the independent per-record processing requirement.
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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.