The answer is to create a Glue DataBrew recipe and schedule the job using a cron expression. This is the most cost-effective approach because DataBrew natively supports job scheduling with standard cron syntax, allowing you to run transformations like filtering rows and adding calculated columns on a recurring basis without provisioning or paying for any additional orchestration services like AWS Glue workflows or Amazon EventBridge rules. On the AWS Certified Data Engineer Associate DEA-C01 exam, this question tests your understanding of native scheduling capabilities versus over-engineered solutions; a common trap is to think you need a separate scheduler or Lambda function when DataBrew’s built-in cron scheduling is sufficient and more economical. Remember the memory tip: “Cron is the cron-job for DataBrew—no extra brew required.”
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 uses AWS Glue DataBrew to clean and transform data for analytics. The source data is in Parquet format in Amazon S3. The transformation includes filtering rows and adding calculated columns. What is the MOST cost-effective way to run these transformations on a schedule?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Create a Glue DataBrew recipe and schedule the job using a cron expression
DataBrew jobs can be scheduled using a cron expression. This is the native way to run transformations automatically without additional services.
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.
✗
Use Amazon EMR with Spark
Why it's wrong here
EMR adds cluster management overhead and cost.
✓
Create a Glue DataBrew recipe and schedule the job using a cron expression
Why this is correct
DataBrew supports scheduling directly.
Related concept
Static NAT maps one inside address to one outside address.
✗
Create an AWS Lambda function triggered by S3 events
Why it's wrong here
Lambda has time limits and is not designed for interactive data preparation.
✗
Use AWS Glue ETL with PySpark
Why it's wrong here
Glue ETL is more expensive and complex for simple transformations.
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: Create a Glue DataBrew recipe and schedule the job using a cron expression — DataBrew jobs can be scheduled using a cron expression. This is the native way to run transformations automatically without additional services.
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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