DEA-C01 Data Ingestion and Transformation Practice Question
A company is using Amazon Kinesis Data Firehose to ingest data into Amazon S3. The data must be transformed from JSON to Parquet format before delivery. Which feature should be enabled on the Firehose delivery stream?
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
✓
Format conversion (Parquet/ORC)
Amazon Kinesis Data Firehose has a built-in format conversion feature that can automatically convert input data from JSON to Parquet or ORC format before delivery to Amazon S3. Option A (Amazon Kinesis Data Analytics) is for real-time stream processing, not format conversion within Firehose. Option B (Amazon S3 event notifications) triggers notifications on S3 events, not data transformation. Option D (AWS Lambda transformation) allows custom code for data transformation but is not specifically for converting JSON to Parquet; the built-in format conversion is the appropriate feature for this task.
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 Analytics
Why it's wrong here
Kinesis Data Analytics performs SQL or Apache Flink stream processing, not record-by-record format conversion within a Firehose delivery stream. It is tempting because it handles real-time transformation of streaming data, and would be correct when you need continuous analytics, aggregation or enrichment rather than converting JSON records to Parquet on delivery.
- ✗
Amazon S3 event notifications
Why it's wrong here
S3 event notifications fire after objects land in the bucket, so they cannot transform records before Firehose delivers them. They are tempting because they trigger downstream processing on new S3 objects, and would be correct for kicking off post-delivery workflows such as Lambda or SQS consumers, not in-flight format conversion.
- ✓
Format conversion (Parquet/ORC)
Why this is correct
Format conversion performs schema-aware JSON-to-Parquet transcoding inside the Firehose delivery stream, using a referenced AWS Glue Data Catalog table to map source fields to Parquet columns. This satisfies the stem's requirement that records be transformed before delivery, removing the need for downstream ETL or Lambda-based conversion.
- ✗
AWS Lambda transformation
Why it's wrong here
Lambda transformation invokes a function per batch, which can convert JSON to Parquet, but the stem's format conversion is natively handled by Firehose's record format conversion using a Glue table schema. Lambda is tempting for arbitrary custom processing, and would be right for bespoke enrichment or filtering.
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
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