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Data Ingestion and TransformationeasyMultiple ChoiceObjective-mapped

DEA-C01 Data Ingestion and Transformation Practice Question

A data engineer needs to ingest data from an Amazon S3 bucket into an Amazon Redshift table on a daily schedule. The data is in CSV format and the schema matches. Which service is simplest for this batch ingestion?

⚠ Common exam trap

The trap here is that candidates may overcomplicate the solution by choosing AWS Glue or Data Pipeline, forgetting that Redshift's native COPY command is purpose-built for high-speed, parallel batch ingestion from S3 with minimal configuration.

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

Amazon Redshift COPY command

The Amazon Redshift COPY command is the simplest and most efficient method for batch loading data from Amazon S3 into Redshift when the schema matches and the data is in CSV format. It leverages Redshift's massively parallel processing (MPP) architecture to read data directly from S3, automatically handling compression, encryption, and error logging without requiring any intermediate services or custom code.

Answer analysis

Option-by-option breakdown

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

  • Amazon Redshift COPY command

    Why this is correct

    Direct and optimized for loading from S3.

  • AWS Glue ETL job with JDBC connection

    Why it's wrong here

    Works but overkill for simple CSV load.

  • AWS Data Pipeline

    Why it's wrong here

    AWS Data Pipeline requires defining a pipeline with activities, schedules, and preconditions, adding operational overhead for a simple daily CSV load where the schema already matches. It is tempting because Data Pipeline is designed for orchestrating complex ETL workflows across multiple AWS services, making it a correct choice when transformation logic or cross-service dependencies are needed.

  • Amazon Athena CREATE TABLE AS SELECT

    Why it's wrong here

    Athena does not load into Redshift.

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

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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.