Quick Answer
The answer is the Relationalize transformation. This AWS Glue transformation is the correct choice because it is purpose-built to flatten nested JSON structures and arrays into a tabular, relational format, automatically creating separate tables for each nested level and linking them with foreign keys. On the AWS Certified Data Engineer Associate DEA-C01 exam, this question tests your understanding of Glue’s specialized ETL transforms for semi-structured data, a common scenario when preparing data for Athena queries. A frequent trap is confusing Relationalize with DropNullFields or Map—remember that Relationalize handles structural complexity, not data cleaning or simple mapping. For a quick memory tip, think “Relationalize = Relational + flatten” to recall that it converts nested JSON into relational tables.
This DEA-C01 practice question tests your understanding of data ingestion and transformation. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
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?
Map
Why wrong: Map applies a function to each record, not for flattening.
Relationalize
Relationalize transforms nested JSON into relational tables suitable for querying.
Filter
Why wrong: Filter selects records based on a condition, does not transform structure.
DropNullFields
Why wrong: DropNullFields removes fields with null values, does not flatten nested structures.
Answer choices
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 into relational tables. Option A (DropNullFields) removes nulls; Option C (Map) applies a function; Option D (Filter) selects rows.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
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.
Related concept
Read the scenario before looking for a memorised answer.
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.
Common exam traps
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Detailed technical explanation
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
A media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
What to study next
Identify which DEA-C01 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
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FAQ
Data Ingestion and Transformation — This question tests Data Ingestion and Transformation — Read the scenario before looking for a memorised answer..
The correct answer is: Relationalize — The Relationalize transformation is specifically designed to flatten nested JSON into relational tables. Option A (DropNullFields) removes nulls; Option C (Map) applies a function; Option D (Filter) selects rows.
Identify which DEA-C01 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
Read the scenario before looking for a memorised answer.
About these practice questions
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Same concept, more angles
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?
easyWhy 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.
Last reviewed: Jun 20, 2026
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.
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