DEA-C01 Data Ingestion and Transformation Practice Question
This DEA-C01 practice question tests your understanding of data ingestion and transformation. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. 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 is using Amazon Kinesis Data Firehose to deliver streaming data to an Amazon S3 bucket. The data is delivered in JSON format. The company wants to convert the data to Apache Parquet format before delivery to reduce storage costs and improve query performance. How can this be achieved?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Use the AWS Glue Data Catalog to define a schema and configure Firehose to use it for Parquet conversion.
Option B is correct because Kinesis Data Firehose can convert the input data to Parquet or ORC format using a schema from the AWS Glue Data Catalog. Option A is incorrect because Firehose does not support a built-in transformation to Parquet without a schema. Option C is incorrect because Lambda can be used for custom transformations, but Firehose natively supports Parquet conversion using Glue. Option D is incorrect because Athena is a query service, not a transformation service.
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.
✗
Deliver data to S3 as JSON, then use Amazon Athena to convert to Parquet.
Why it's wrong here
Athena can query data but does not convert it to Parquet; you would need an ETL job.
✓
Use the AWS Glue Data Catalog to define a schema and configure Firehose to use it for Parquet conversion.
Why this is correct
This is the recommended approach for converting streaming data to Parquet in Firehose.
Related concept
Static NAT maps one inside address to one outside address.
✗
Write an AWS Lambda function to transform the data to Parquet and deliver it to S3.
Why it's wrong here
While possible, this is more complex and not the native Firehose capability.
✗
Configure the Firehose stream to convert data to Parquet automatically without any additional setup.
Why it's wrong here
Firehose requires a schema from the Glue Data Catalog to convert to Parquet.
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 startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
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: Use the AWS Glue Data Catalog to define a schema and configure Firehose to use it for Parquet conversion. — Option B is correct because Kinesis Data Firehose can convert the input data to Parquet or ORC format using a schema from the AWS Glue Data Catalog. Option A is incorrect because Firehose does not support a built-in transformation to Parquet without a schema. Option C is incorrect because Lambda can be used for custom transformations, but Firehose natively supports Parquet conversion using Glue. Option D is incorrect because Athena is a query service, not a transformation service.
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.
What is the key concept behind this question?
Static NAT maps one inside address to one outside address.
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Question Discussion
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