The answer is to set up S3 event notifications that invoke an AWS Lambda function, which triggers a Glue job for each new object and passes the object key so the job processes only that file. This approach directly implements incremental Glue processing for late-arriving data, because instead of scanning the entire S3 bucket daily, the job handles only newly arrived files—even those up to three days late—dramatically reducing both processing time and cost. On the AWS Certified Data Engineer Associate DEA-C01 exam, this scenario tests your understanding of event-driven architectures versus full-scan batch jobs; a common trap is choosing to increase job capacity or switch to Amazon EMR, which add complexity without solving the root inefficiency. Remember the key insight: for streaming-like ingestion with late data, trigger on the event, not on a schedule. Memory tip: "Event-driven Glue, not full-bucket chew."
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 social media company ingests user activity data from multiple sources into Amazon S3. The data is in JSON format and includes fields: user_id, activity_type, timestamp, and metadata. The company wants to transform this data into a columnar format (Parquet) partitioned by date and activity_type for efficient querying with Amazon Athena. The pipeline must handle data that arrives up to 3 days late. Currently, a daily AWS Glue ETL job scans the entire S3 bucket for new files, transforms them, and writes to a separate output bucket. The job is taking longer as data volume grows, and the team wants to reduce processing time and cost. What should the engineer do?
Increase the number of DPUs for the Glue job to process data faster.
Why wrong: This increases cost and may not scale linearly; still scans all files.
B
Use AWS Glue partition projection and schema inference to reduce scan time.
Why wrong: Partition projection helps Athena queries but does not reduce Glue job processing time.
C
Replace AWS Glue with Amazon EMR and use Spark to process data in parallel.
Why wrong: EMR requires cluster management and is overkill for this use case.
D
Set up S3 event notifications to invoke an AWS Lambda function that triggers a Glue job for each new object, passing the object key so the job processes only that file.
This enables incremental processing, reduces scan time, and is cost-effective.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Set up S3 event notifications to invoke an AWS Lambda function that triggers a Glue job for each new object, passing the object key so the job processes only that file.
Option B is correct: Using S3 event notifications to trigger a Lambda function that starts a Glue job for each new file allows incremental processing, reducing scan time. Option A (increase capacity) does not address the root cause. Option C (EMR) adds complexity. Option D (partition projection) does not help with transformation.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
✗
Increase the number of DPUs for the Glue job to process data faster.
Why it's wrong here
This increases cost and may not scale linearly; still scans all files.
✗
Use AWS Glue partition projection and schema inference to reduce scan time.
Why it's wrong here
Partition projection helps Athena queries but does not reduce Glue job processing time.
✗
Replace AWS Glue with Amazon EMR and use Spark to process data in parallel.
Why it's wrong here
EMR requires cluster management and is overkill for this use case.
✓
Set up S3 event notifications to invoke an AWS Lambda function that triggers a Glue job for each new object, passing the object key so the job processes only that file.
Why this is correct
This enables incremental processing, reduces scan time, and is cost-effective.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Detailed technical explanation
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
KKey Concepts to Remember
Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.
Use explanations to understand the rule behind the answer.
TExam Day Tips
→Underline the problem statement mentally.
→Watch for words such as best, first, most likely and least administrative effort.
→Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
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.
Identify which DEA-C01 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
Data Ingestion and Transformation — This question tests Data Ingestion and Transformation — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Set up S3 event notifications to invoke an AWS Lambda function that triggers a Glue job for each new object, passing the object key so the job processes only that file. — Option B is correct: Using S3 event notifications to trigger a Lambda function that starts a Glue job for each new file allows incremental processing, reducing scan time. Option A (increase capacity) does not address the root cause. Option C (EMR) adds complexity. Option D (partition projection) does not help with transformation.
What should I do if I get this DEA-C01 question wrong?
Identify which DEA-C01 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Question Discussion
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