This MLA-C01 practice question tests your understanding of data preparation for machine learning. 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.
An organization stores raw data in Amazon S3 as CSV files. They need to perform serverless data transformation and convert the data to Parquet format for efficient ML training. Which AWS service is most appropriate?
AWS Glue
AWS Glue is a serverless ETL service that can transform data formats.
Amazon EMR
Why wrong: EMR requires provisioning clusters, not serverless.
Amazon Athena
Why wrong: Athena is an interactive query service, not designed for data transformation.
Amazon Redshift
Why wrong: Redshift is a data warehouse, not a transformation service.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
AWS Glue
AWS Glue is the most appropriate service because it is a fully managed, serverless ETL service designed specifically for data transformation tasks like converting CSV to Parquet. It automatically handles schema inference, data partitioning, and optimization for ML training workloads without requiring infrastructure management.
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.
AWS Glue
Why this is correct
AWS Glue is a serverless ETL service that can transform data formats.
Related concept
Read the scenario before looking for a memorised answer.
Amazon EMR
Why it's wrong here
EMR requires provisioning clusters, not serverless.
Amazon Athena
Why it's wrong here
Athena is an interactive query service, not designed for data transformation.
Amazon Redshift
Why it's wrong here
Redshift is a data warehouse, not a transformation service.
Common exam traps
The trap here is that candidates often confuse Amazon Athena's ability to query Parquet data with the ability to transform data into Parquet, but Athena is a query engine, not an ETL transformation service.
Detailed technical explanation
AWS Glue uses Apache Spark under the hood for distributed data processing, and its DynamicFrame abstraction handles schema evolution and data type inference automatically. When converting CSV to Parquet, Glue can optimize output by partitioning data based on columns (e.g., date or region), which significantly improves query performance in ML training pipelines. A real-world scenario is an organization with terabytes of raw CSV logs that need to be converted to columnar Parquet for SageMaker training, where Glue's serverless nature avoids cluster management overhead.
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 exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Data Preparation for Machine Learning — study guide chapter
Learn the concepts, then practise the questions
Data Preparation for Machine Learning practice questions
Targeted practice on this topic area only
All MLA-C01 questions
507 questions across all exam domains
AWS Certified Machine Learning Engineer Associate MLA-C01 study guide
Full concept coverage aligned to exam objectives
MLA-C01 practice test guide
How to use practice tests most effectively before exam day
Related practice questions
Use these pages to review the topic behind this question. This is how one missed question becomes focused revision.
Practise MLA-C01 questions linked to Data Preparation for Machine Learning.
Practise MLA-C01 questions linked to ML Model Development.
Practise MLA-C01 questions linked to Deployment and Orchestration of ML Workflows.
Practise MLA-C01 questions linked to ML Solution Monitoring, Maintenance and Security.
Practise MLA-C01 questions linked to MLA-C01 fundamentals.
Practise MLA-C01 questions linked to MLA-C01 scenario.
Practise MLA-C01 questions linked to MLA-C01 troubleshooting.
Practice this exam
Short sessions build daily habit. Longer sessions build exam-day stamina. Try a timed session to simulate real conditions.
FAQ
Data Preparation for Machine Learning — This question tests Data Preparation for Machine Learning — Read the scenario before looking for a memorised answer..
The correct answer is: AWS Glue — AWS Glue is the most appropriate service because it is a fully managed, serverless ETL service designed specifically for data transformation tasks like converting CSV to Parquet. It automatically handles schema inference, data partitioning, and optimization for ML training workloads without requiring infrastructure management.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Read the scenario before looking for a memorised answer.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
Last reviewed: Jun 24, 2026
This MLA-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 MLA-C01 exam.
Question Discussion
Share a tip, memory trick, or ask about the reasoning behind this question. Do not post real exam questions, leaked content, braindumps, or copyrighted exam material. Comments are moderated and may be removed without notice.
Sign in to join the discussion.