DEA-C01 Data Ingestion and Transformation Practice Question
A company uses Kinesis Data Firehose to deliver streaming data to S3. They need to transform the data by adding a timestamp and removing sensitive fields. Which TWO approaches can achieve this?
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
✓
Use AWS Glue ETL to process data after delivery to S3
Options C and E are correct. E: Kinesis Firehose can invoke a Lambda function to transform records (add timestamp, remove fields) before delivery to S3. C: AWS Glue ETL can process data after it is stored in S3, performing transformations like adding timestamps and removing sensitive fields. Option A is incorrect because Kinesis Data Analytics is for real-time analytics, not for adding timestamps or removing fields in the Firehose pipeline. Option B is incorrect because S3 Select is used to retrieve subsets of data using SQL, not to transform data. Option D is incorrect because Redshift Spectrum is for querying data in S3, not for transforming it.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use Kinesis Data Analytics to transform the stream
Why it's wrong here
Kinesis Data Analytics is for real-time analytics, not simple transformations.
- ✗
Use S3 Select to transform data at rest
Why it's wrong here
S3 Select is for querying, not transforming.
- ✓
Use AWS Glue ETL to process data after delivery to S3
Why this is correct
Glue can transform data after it is stored in S3.
- ✗
Use Amazon Redshift Spectrum to transform data
Why it's wrong here
Redshift Spectrum is for querying external data.
- ✓
Configure a Lambda function as a data transformation in Firehose
Why this is correct
Lambda can transform records before delivery.
Quick reference
AWS S3 Storage Class Comparison
| Storage Class | Min Duration | Retrieval | Use Case |
|---|---|---|---|
| S3 Standard | None | Immediate | Frequently accessed data |
| S3 Standard-IA | 30 days | Immediate | Infrequent access, rapid retrieval |
| S3 One Zone-IA | 30 days | Immediate | Non-critical infrequent data |
| S3 Intelligent-Tiering | None | Immediate–hours | Unknown or changing access patterns |
| S3 Glacier Instant | 90 days | Milliseconds | Archive with instant retrieval |
| S3 Glacier Flexible | 90 days | Minutes–hours | Archive, flexible retrieval |
| S3 Glacier Deep Archive | 180 days | Hours | Long-term compliance archive |
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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.