DEA-C01 Data Ingestion and Transformation Practice Question
A company uses Amazon Kinesis Data Firehose to ingest JSON logs from multiple sources into an S3 data lake. The data is then consumed by Amazon Athena for analysis. Recently, some queries have been failing with the error 'HIVE_BAD_DATA: Field xyz's type is an unsupported type'. The firehose delivery stream transforms the data using a Lambda function that converts timestamps to Unix epoch. What is the MOST likely cause of the query failure?
⚠ Common exam trap
The DEA-C01 exam often tests the misconception that Athena errors are always due to file format or permissions, when in reality schema-on-read type inference from inconsistent data is a common pitfall.
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
✓
Some records contain timestamps that were not converted to epoch, so Athena infers the column as a string.
The error 'HIVE_BAD_DATA: Field xyz's type is an unsupported type' occurs when Athena's schema inference encounters inconsistent data types for the same column. Since the Lambda function converts timestamps to Unix epoch, but some records may have failed conversion (e.g., due to malformed input or Lambda errors), those records retain the original string timestamp. Athena then sees a mix of numeric epoch values and string timestamps, causing it to infer the column as a string type, which is unsupported for the expected numeric operations in the query.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Some records contain timestamps that were not converted to epoch, so Athena infers the column as a string.
Why this is correct
Inconsistent data types in a column cause Athena to default to string, leading to type mismatch when queried.
- ✗
The data is in JSON format instead of Parquet.
Why it's wrong here
Athena supports JSON; the error is about type, not format.
- ✗
The S3 partitions are not registered in the Glue Data Catalog.
Why it's wrong here
Missing partitions cause 'Partition not found' errors, not type mismatch.
- ✗
The IAM role for Firehose does not have permission to write to S3.
Why it's wrong here
That would cause write failures, not query errors.
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
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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.