DEA-C01 Data Ingestion and Transformation Practice Question
A company uses Amazon Kinesis Data Firehose to deliver data to an Amazon S3 bucket. The data is in JSON format and contains a 'timestamp' field with a Unix epoch value. The company wants to partition the S3 objects by year, month, day, and hour based on the timestamp. What is the MOST efficient method to achieve this?
⚠ Common exam trap
It's easy for candidates to confuse Firehose's static custom prefix (which uses delivery time) with dynamic partitioning (which uses record content), causing candidates to pick option B as a simpler solution.
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 the dynamic partitioning feature of Kinesis Data Firehose with inline parsing to extract the timestamp and create the S3 prefix.
Kinesis Data Firehose dynamic partitioning with inline parsing extracts the 'timestamp' field from each JSON record and uses it to build the S3 prefix (year/month/day/hour) automatically as records are delivered. This is the native, serverless, most efficient approach because Firehose handles the partitioning logic per-record without any additional compute services. It also supports JQ expressions for extracting and formatting the timestamp into the desired prefix pattern.
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 the dynamic partitioning feature of Kinesis Data Firehose with inline parsing to extract the timestamp and create the S3 prefix.
Why this is correct
Dynamic partitioning with inline parsing extracts the timestamp field directly within Firehose and derives year/month/day/hour prefixes automatically, avoiding custom Lambda transformation or downstream reprocessing. This satisfies the requirement for the most efficient, serverless partitioning method without managing extra compute.
- ✗
Configure a custom S3 prefix in Firehose using the 'YYYY/MM/dd/HH' format based on the current time.
Why it's wrong here
Firehose's custom prefix uses the delivery time, not the record's timestamp field, so objects land under the wrong year/month/day/hour. It is tempting because static prefixes like this are the standard way to organise output by arrival period when ingestion time equals event time.
- ✗
Use an AWS Glue ETL job to read from Firehose, partition, and write to S3.
Why it's wrong here
A Glue ETL job reads from Firehose streams only indirectly and adds a separate processing stage, duplicating work Firehose already performs. It is tempting because Glue is the usual tool for repartitioning existing S3 data during batch transformation, not for dynamic partitioning at delivery.
- ✗
Use Amazon Athena to run a CTAS query that partitions the data by timestamp.
Why it's wrong here
Athena CTAS queries existing S3 data and writes new partitioned tables; it cannot intercept records before Firehose delivers them. It is tempting because CTAS is the standard way to repartition an already-landed dataset into year/month/day/hour prefixes for query performance.
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 |
Go deeper
Related to this question
About these practice questions
This DEA-C01 question is part of Courseiva's 1,321-question bank — original exam-style content with full explanations and wrong-answer analysis, never real exam questions or exam dumps. Learn why practice questions differ from exam dumps →
JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Amazon Web Services exam blueprint
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.