Courseiva
Question 102 of 1,711
Data Ingestion and TransformationmediumMultiple ChoiceObjective-mapped

DEA-C01 Data Ingestion and Transformation Practice Question

A company needs to transform JSON data from an Amazon S3 bucket into Parquet format and load it into an Amazon Redshift cluster. The transformation includes joining with a reference table stored in Amazon RDS. Which AWS service is BEST suited for this task?

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

AWS Glue ETL job

(AWS Glue ETL job) is the best choice because it natively integrates with S3, RDS, and Redshift. Glue can read JSON from S3, connect to RDS via JDBC to join with the reference table, transform the data to Parquet using its built-in converter, and write directly to Redshift. Option A (AWS Data Pipeline) is older and less integrated for this purpose. Option C (Amazon Athena) can query S3 and convert to Parquet but cannot natively join with RDS without additional services. Option D (Amazon EMR with Spark) is possible but requires more setup and maintenance.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • AWS Data Pipeline

    Why it's wrong here

    Data Pipeline is a legacy service; Glue is more modern for ETL.

  • AWS Glue ETL job

    Why this is correct

    Glue ETL jobs can read from S3, connect to RDS via JDBC, transform, and write to Redshift efficiently.

  • Amazon Athena

    Why it's wrong here

    Athena queries data in S3 but cannot directly connect to RDS for joins in a single query.

  • Amazon EMR with Spark

    Why it's wrong here

    Amazon EMR with Spark is a powerful platform for big data processing, making it tempting for complex transformations and custom code execution on petabyte-scale datasets. However, for this specific scenario, EMR introduces operational overhead by requiring cluster management, which is not optimal for a standard, recurring ETL pipeline from S3 to Redshift with an RDS join. A more serverless or fully managed ETL service would minimise administrative burden and align better with the 'BEST suited' criterion.

Quick reference

AWS S3 Storage Class Comparison

Storage ClassMin DurationRetrievalUse Case
S3 StandardNoneImmediateFrequently accessed data
S3 Standard-IA30 daysImmediateInfrequent access, rapid retrieval
S3 One Zone-IA30 daysImmediateNon-critical infrequent data
S3 Intelligent-TieringNoneImmediate–hoursUnknown or changing access patterns
S3 Glacier Instant90 daysMillisecondsArchive with instant retrieval
S3 Glacier Flexible90 daysMinutes–hoursArchive, flexible retrieval
S3 Glacier Deep Archive180 daysHoursLong-term compliance archive

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 →

How Courseiva writes practice questions · Editorial policy

Last reviewed: Jun 20, 2026

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.

Loading comments…

Sign in to join the discussion.

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.