The answer is to use AWS Lambda triggered by S3 events, or combine Lambda with AWS Glue. This is correct because S3 event notifications can directly invoke a Lambda function each time a new JSON object lands, allowing the function to convert the data to Parquet format and write it to partitioned paths like year/month/day using the AWS SDK. Alternatively, Glue can be triggered by S3 events via a workflow to perform the same conversion at scale, offering a serverless, low-overhead solution. On the AWS Certified Data Engineer Associate DEA-C01 exam, this question tests your understanding of event-driven architectures and cost-effective data transformation—common traps include choosing Kinesis Firehose (which cannot easily partition by custom date fields) or EMR (which requires cluster management). Memory tip: think "S3 event + Lambda = instant partition conversion," or recall that Glue is the heavy lifter for schema-on-read, while Lambda handles lightweight, per-object transformations.
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 ingests IoT data into an S3 bucket using AWS IoT Core rules. The data is in JSON format, and each record is about 500 bytes. The data volume is 5 GB per day. The company wants to convert the data to Parquet format and partition it by year/month/day. Which TWO AWS services can be used together to achieve this with minimal operational overhead?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
AWS Glue ETL job triggered by S3 event
Options B and E are correct. S3 Events can trigger Lambda, and Lambda can convert JSON to Parquet and write to partitioned paths. AWS Glue can also be triggered by S3 events via a workflow, but the combination of Lambda + Glue (option E) works as Glue can read from the landing zone and write partitioned Parquet. Option A (Kinesis Firehose) can convert to Parquet but cannot partition by year/month/day easily. Option C (EMR) requires cluster management. Option D (Athena) is for querying, not transformation.
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.
✗
Amazon Athena CTAS query
Why it's wrong here
Athena is for querying, not for continuous transformation of incoming data.
✓
AWS Glue ETL job triggered by S3 event
Why this is correct
Glue can be triggered by S3 events (via Lambda or EventBridge) and perform the conversion and partitioning.
Related concept
Static NAT maps one inside address to one outside address.
✓
AWS Lambda function triggered by S3 event
Why this is correct
Lambda can perform the conversion and write to partitioned S3 paths.
Related concept
Static NAT maps one inside address to one outside address.
Amazon Kinesis Data Firehose with Parquet conversion
Why it's wrong here
Firehose can convert to Parquet but does not support custom partitioning like year/month/day without additional Lambda.
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: AWS Glue ETL job triggered by S3 event — Options B and E are correct. S3 Events can trigger Lambda, and Lambda can convert JSON to Parquet and write to partitioned paths. AWS Glue can also be triggered by S3 events via a workflow, but the combination of Lambda + Glue (option E) works as Glue can read from the landing zone and write partitioned Parquet. Option A (Kinesis Firehose) can convert to Parquet but cannot partition by year/month/day easily. Option C (EMR) requires cluster management. Option D (Athena) is for querying, not transformation.
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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