The answer is that some records contain timestamps that were not converted to epoch, causing Athena to infer the column as a string. This HIVE_BAD_DATA error occurs because Athena’s schema inference expects a numeric type for the timestamp field, but when a Lambda function in Kinesis Firehose fails to convert certain timestamps to Unix epoch, those records remain as strings, creating a type mismatch. On the AWS Certified Data Engineer Associate DEA-C01 exam, this tests your understanding of how Athena’s schema-on-read works with heterogeneous data in Firehose—a common trap is assuming the error is due to partitions or permissions, but the root cause is inconsistent data transformation. Remember: if your Firehose Lambda conversion is partial, Athena sees mixed types and throws HIVE_BAD_DATA. Memory tip: “Mixed epoch types break the inference—if it’s not all numbers, expect the error.”
DEA-C01 Data Ingestion and Transformation Practice Question
This DEA-C01 practice question tests your understanding of data ingestion and transformation. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. 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 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?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "most likely"
Why it matters: Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
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 indicates that the data type detected by Athena's schema inference does not match the actual data. Since the Lambda function converts timestamps to Unix epoch (a number), Athena may infer the column as a string due to some records not being converted properly. Option A is wrong because partitions do not cause this error. Option B is wrong because S3 permissions would cause a different error. Option D is wrong because data format is likely compatible.
Key principle: NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated.
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.
Clue confirmation
The clue word "most likely" in the question point toward this answer.
Related concept
Static NAT maps one inside address to one outside address.
✗
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.
Common exam traps
Common exam trap: NAT rules depend on direction and matching traffic
NAT is not only about the public address. The inside/outside interface roles and the ACL or rule that matches traffic are just as important.
Detailed technical explanation
How to think about this question
NAT questions usually test address translation, overload/PAT behaviour, static mappings and whether the right traffic is being translated. Read the interface direction and address terms carefully.
KKey Concepts to Remember
Static NAT maps one inside address to one outside address.
PAT allows many inside hosts to share one public address using ports.
Inside local and inside global describe the private and translated addresses.
NAT ACLs identify traffic for translation, not always security filtering.
TExam Day Tips
→Identify inside and outside interfaces first.
→Check whether the scenario needs static NAT, dynamic NAT or PAT.
→Do not confuse NAT matching ACLs with normal packet-filtering intent.
Key takeaway
NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated.
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.
What to study next
Got this wrong? Here's your next step.
Review the four NAT address types (inside local, inside global, outside local, outside global), PAT port overload, and static vs dynamic NAT use cases. Then practise related DEA-C01 NAT questions on configuration and troubleshooting.
Data Ingestion and Transformation — This question tests Data Ingestion and Transformation — Static NAT maps one inside address to one outside address..
What is the correct answer to this question?
The correct answer is: Some records contain timestamps that were not converted to epoch, so Athena infers the column as a string. — The error indicates that the data type detected by Athena's schema inference does not match the actual data. Since the Lambda function converts timestamps to Unix epoch (a number), Athena may infer the column as a string due to some records not being converted properly. Option A is wrong because partitions do not cause this error. Option B is wrong because S3 permissions would cause a different error. Option D is wrong because data format is likely compatible.
What should I do if I get this DEA-C01 question wrong?
Review the four NAT address types (inside local, inside global, outside local, outside global), PAT port overload, and static vs dynamic NAT use cases. Then practise related DEA-C01 NAT questions on configuration and troubleshooting.
Are there clue words in this question I should notice?
Yes — watch for: "most likely". Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
What is the key concept behind this question?
Static NAT maps one inside address to one outside address.
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