- A
AWS Glue
Glue ETL can transform and enrich data from streams and databases.
- B
Amazon Kinesis Data Firehose
Why wrong: Firehose cannot perform enrichment with a relational database.
- C
Amazon Athena
Why wrong: Athena is for querying, not ETL.
- D
Amazon SageMaker
Why wrong: SageMaker is for ML models, not data pipeline.
- E
Amazon Kinesis Data Streams
Ingests streaming social media data.
Question 1,558 of 1,755
MLS-C01 Data Engineering Practice Question
This MLS-C01 practice question tests your understanding of data engineering. 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 data engineering team is designing a data pipeline to process streaming data from social media feeds. The data must be deduplicated, enriched with customer information from a relational database, and stored in Amazon S3 in Parquet format. Which AWS services should the team use to build this pipeline? (Select TWO.)
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
✓
AWS Glue
AWS Glue is correct because it provides a serverless ETL service that can transform streaming data stored in Amazon S3 into Parquet format. It can also connect to a relational database via JDBC to enrich the data with customer information, and its built-in deduplication capabilities (e.g., using DropDuplicates in PySpark) handle the deduplication requirement.
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.
- ✓
AWS Glue
Why this is correct
Glue ETL can transform and enrich data from streams and databases.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Amazon Kinesis Data Firehose
Why it's wrong here
Firehose cannot perform enrichment with a relational database.
- ✗
Amazon Athena
Why it's wrong here
Athena is for querying, not ETL.
- ✗
Amazon SageMaker
Why it's wrong here
SageMaker is for ML models, not data pipeline.
- ✓
Amazon Kinesis Data Streams
Why this is correct
Ingests streaming social media data.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
AWS often tests the distinction between data ingestion services (Kinesis Data Firehose) and data processing/ETL services (AWS Glue), leading candidates to mistakenly select Firehose for deduplication and enrichment tasks that it cannot natively perform.
Detailed technical explanation
How to think about this question
AWS Glue uses Apache Spark under the hood, allowing it to perform complex transformations like deduplication via dropDuplicates() and enrichment via joins with data from a relational database using JDBC connectors. The Parquet format is columnar and optimized for compression and query performance, and Glue can convert streaming data buffered in S3 from formats like JSON or CSV to Parquet during ETL runs. In real-world scenarios, Glue can be triggered by new data arriving in S3 via event notifications, making it suitable for near-real-time processing of streaming data.
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: AWS Glue — AWS Glue is correct because it provides a serverless ETL service that can transform streaming data stored in Amazon S3 into Parquet format. It can also connect to a relational database via JDBC to enrich the data with customer information, and its built-in deduplication capabilities (e.g., using DropDuplicates in PySpark) handle the deduplication requirement.
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.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
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Last reviewed: Jul 4, 2026
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