Question 1,137 of 1,786
Data Ingestion and TransformationmediumMultiple SelectObjective-mapped

Data Lake Ingestion: Using Kinesis Firehose, AWS DMS, and AWS Glue

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 is building a data lake on Amazon S3. They need to ingest data from multiple sources, including relational databases, streaming data, and log files. Which THREE AWS services can be used to ingest data into the data lake?

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 Kinesis Data Firehose

Amazon Kinesis Data Firehose is a fully managed service for streaming data ingestion that can capture, transform, and load streaming data into Amazon S3 in near real-time. It supports sources like Amazon CloudWatch Logs, AWS IoT, and custom producers via the Kinesis Agent, making it ideal for log files and streaming data.

Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.

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 Kinesis Data Firehose

    Why this is correct

    Ingests streaming data into S3.

    Related concept

    Read the scenario before looking for a memorised answer.

  • AWS Database Migration Service (DMS)

    Why this is correct

    Can migrate databases to S3 in full load or CDC.

    Related concept

    Read the scenario before looking for a memorised answer.

  • Amazon Athena

    Why it's wrong here

    Query service, not ingestion.

  • Amazon Redshift Spectrum

    Why it's wrong here

    Query service for Redshift on S3 data.

  • AWS Glue

    Why this is correct

    ETL service that can move data from various sources to S3.

    Related concept

    Read the scenario before looking for a memorised answer.

Common exam traps

Common exam trap: answer the scenario, not the keyword

The trap here is confusing query engines (Athena, Redshift Spectrum) with ingestion services, as candidates often assume any service that touches S3 can be used for data loading.

Detailed technical explanation

How to think about this question

Kinesis Data Firehose can optionally transform data using AWS Lambda before delivery to S3, and it supports delivery to S3 in Apache Parquet or ORC format for optimized querying. AWS DMS can perform ongoing replication from relational databases using change data capture (CDC) to keep the data lake synchronized with source changes. AWS Glue provides both batch ETL jobs and a visual interface for building ingestion pipelines, and it can catalog the ingested data in the Glue Data Catalog for use by services like Athena.

KKey Concepts to Remember

  • Read the scenario before looking for a memorised answer.
  • Find the constraint that changes the correct option.
  • Eliminate answers that are true in general but not in this case.

TExam Day Tips

  • Watch for words such as best, first, most likely and least administrative effort.
  • Review why wrong options are wrong, not only why the correct option is correct.

Key takeaway

Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.

Real-world example

How this comes up in practice

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.

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

What to study next

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FAQ

Questions learners often ask

What does this DEA-C01 question test?

Data Ingestion and Transformation — This question tests Data Ingestion and Transformation — Read the scenario before looking for a memorised answer..

What is the correct answer to this question?

The correct answer is: Amazon Kinesis Data Firehose — Amazon Kinesis Data Firehose is a fully managed service for streaming data ingestion that can capture, transform, and load streaming data into Amazon S3 in near real-time. It supports sources like Amazon CloudWatch Logs, AWS IoT, and custom producers via the Kinesis Agent, making it ideal for log files and streaming data.

What should I do if I get this DEA-C01 question wrong?

Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.

What is the key concept behind this question?

Read the scenario before looking for a memorised answer.

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Last reviewed: Jul 4, 2026

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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.