- A
Amazon Kinesis Data Analytics for transformation
Why wrong: Kinesis Data Analytics is for real-time streaming, not batch transformation.
- B
Amazon S3 event notifications to invoke AWS Lambda, which triggers an AWS Glue job
S3 events trigger Lambda, which starts a Glue ETL job; this is event-driven and serverless.
- C
Amazon EMR with automatic scaling
Why wrong: EMR requires cluster management and is less event-driven.
- D
AWS Step Functions to orchestrate the pipeline
Why wrong: Step Functions can orchestrate but is not directly triggered by S3 events without Lambda.
Question 426 of 1,755
MLS-C01 Data Engineering Practice Question
This MLS-C01 practice question tests your understanding of data engineering. This is a configuration task: choose the command set that satisfies every stated requirement. Small differences — like 'secret' vs 'password' or 'transport input ssh' vs 'all' — change whether the answer is correct. 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 building a data pipeline that ingests data from multiple sources into a centralized data lake on Amazon S3. The data must be transformed before it is available for analysis. The pipeline should be event-driven, automatically triggering transformation jobs when new data arrives. Which combination of AWS services should be used?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Amazon S3 event notifications to invoke AWS Lambda, which triggers an AWS Glue job
Option B is correct because Amazon S3 event notifications can be configured to invoke an AWS Lambda function when new objects are created in an S3 bucket. The Lambda function can then trigger an AWS Glue job to perform the necessary data transformations. This creates an event-driven, serverless pipeline that automatically processes data as it arrives, meeting the requirements for a centralized data lake on S3.
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.
- ✗
Amazon Kinesis Data Analytics for transformation
Why it's wrong here
Kinesis Data Analytics is for real-time streaming, not batch transformation.
- ✓
Amazon S3 event notifications to invoke AWS Lambda, which triggers an AWS Glue job
Why this is correct
S3 events trigger Lambda, which starts a Glue ETL job; this is event-driven and serverless.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Amazon EMR with automatic scaling
Why it's wrong here
EMR requires cluster management and is less event-driven.
- ✗
AWS Step Functions to orchestrate the pipeline
Why it's wrong here
Step Functions can orchestrate but is not directly triggered by S3 events without Lambda.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates may choose AWS Step Functions (Option D) because it is a powerful orchestrator, but they overlook that it is not directly event-driven from S3 without an intermediary like Lambda or EventBridge, and it does not perform the actual transformation.
Detailed technical explanation
How to think about this question
Under the hood, S3 event notifications use the S3 API to send events to Lambda via a push-based mechanism, with a default event notification configuration that supports s3:ObjectCreated:* events. AWS Glue jobs can be triggered by Lambda using the boto3 client.start_job_run() API, and the job can read data from S3, transform it using PySpark or Python, and write results back to S3. A real-world scenario where this matters is when data arrives in varying formats (e.g., CSV, JSON, Parquet) and needs to be normalized into a consistent schema for analytics; the event-driven approach ensures zero idle compute costs until data arrives.
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.
TExam Day Tips
- 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 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.
Quick reference
AWS S3 Storage Class Comparison
| Storage Class | Min Duration | Retrieval | Use Case |
|---|---|---|---|
| S3 Standard | None | Immediate | Frequently accessed data |
| S3 Standard-IA | 30 days | Immediate | Infrequent access, rapid retrieval |
| S3 One Zone-IA | 30 days | Immediate | Non-critical infrequent data |
| S3 Intelligent-Tiering | None | Immediate–hours | Unknown or changing access patterns |
| S3 Glacier Instant | 90 days | Milliseconds | Archive with instant retrieval |
| S3 Glacier Flexible | 90 days | Minutes–hours | Archive, flexible retrieval |
| S3 Glacier Deep Archive | 180 days | Hours | Long-term compliance archive |
What to study next
Got this wrong? Here's your next step.
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FAQ
Questions learners often ask
What does this MLS-C01 question test?
Data Engineering — This question tests Data Engineering — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Amazon S3 event notifications to invoke AWS Lambda, which triggers an AWS Glue job — Option B is correct because Amazon S3 event notifications can be configured to invoke an AWS Lambda function when new objects are created in an S3 bucket. The Lambda function can then trigger an AWS Glue job to perform the necessary data transformations. This creates an event-driven, serverless pipeline that automatically processes data as it arrives, meeting the requirements for a centralized data lake on S3.
What should I do if I get this MLS-C01 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jul 4, 2026
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