- A
AWS Database Migration Service (DMS) to Amazon S3, then COPY into Redshift
Correct. AWS DMS supports ongoing replication (CDC) from Oracle to S3, then COPY into Redshift for efficient loading.
- B
Amazon Kinesis Data Streams with a custom producer on Oracle
Why wrong: Incorrect. Amazon Kinesis Data Streams requires a custom producer to capture Oracle changes and does not directly integrate with Oracle for CDC.
- C
AWS Glue with JDBC connection to Oracle, writing to Redshift
Why wrong: Incorrect. AWS Glue with JDBC is batch-oriented and does not support real-time CDC natively.
- D
AWS Lambda reading from Oracle logs and writing to Redshift
Why wrong: Incorrect. AWS Lambda can process events but is not designed for continuous, low-latency CDC from a database; it would require polling or triggers.
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 data engineer is designing a data ingestion pipeline to load data from an on-premises Oracle database into Amazon Redshift. The pipeline must capture changes (inserts, updates, deletes) with low latency and minimal impact on the source database. Which combination of AWS services should the engineer use?
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 Database Migration Service (DMS) to Amazon S3, then COPY into Redshift
Option A is correct because AWS DMS with ongoing replication (change data capture) can capture changes from Oracle with minimal impact and replicate to S3, then COPY into Redshift. Option B is wrong because Kinesis Data Streams requires a custom producer to capture Oracle changes and does not provide native CDC from Oracle databases. Option C is wrong because AWS Glue with JDBC is batch-oriented and does not support real-time change data capture natively. Option D is wrong because AWS Lambda can process events but is not designed for continuous, low-latency CDC from a database and would require polling or triggers.
Key principle: ACLs process entries top to bottom and stop at the first match. Entry order and interface direction matter as much as the permit or deny statement.
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 Database Migration Service (DMS) to Amazon S3, then COPY into Redshift
Why this is correct
Correct. AWS DMS supports ongoing replication (CDC) from Oracle to S3, then COPY into Redshift for efficient loading.
Related concept
Standard ACLs match source addresses.
- ✗
Amazon Kinesis Data Streams with a custom producer on Oracle
Why it's wrong here
Incorrect. Amazon Kinesis Data Streams requires a custom producer to capture Oracle changes and does not directly integrate with Oracle for CDC.
- ✗
AWS Glue with JDBC connection to Oracle, writing to Redshift
Why it's wrong here
Incorrect. AWS Glue with JDBC is batch-oriented and does not support real-time CDC natively.
- ✗
AWS Lambda reading from Oracle logs and writing to Redshift
Why it's wrong here
Incorrect. AWS Lambda can process events but is not designed for continuous, low-latency CDC from a database; it would require polling or triggers.
Common exam traps
Common exam trap: ACLs stop at the first match
ACLs are processed top to bottom. The first matching entry wins, and an implicit deny usually exists at the end.
Detailed technical explanation
How to think about this question
ACL questions test precision: source, destination, protocol, port and direction. A generally correct ACL can still fail if it is applied on the wrong interface or in the wrong direction.
KKey Concepts to Remember
- Standard ACLs match source addresses.
- Extended ACLs can match source, destination, protocol and ports.
- The first matching ACL entry is used.
- There is usually an implicit deny at the end.
TExam Day Tips
- Check inbound versus outbound direction.
- Read the ACL from top to bottom.
- Look for a broader permit or deny above the intended line.
Key takeaway
ACLs process entries top to bottom and stop at the first match. Entry order and interface direction matter as much as the permit or deny statement.
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.
Review ACL processing order, placement rules (standard near destination, extended near source), and inbound vs outbound direction. Study wildcard masks and implicit deny. Then practise related DEA-C01 ACL questions on filtering logic and placement.
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Data Ingestion and Transformation — study guide chapter
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FAQ
Questions learners often ask
What does this DEA-C01 question test?
Data Ingestion and Transformation — This question tests Data Ingestion and Transformation — Standard ACLs match source addresses..
What is the correct answer to this question?
The correct answer is: AWS Database Migration Service (DMS) to Amazon S3, then COPY into Redshift — Option A is correct because AWS DMS with ongoing replication (change data capture) can capture changes from Oracle with minimal impact and replicate to S3, then COPY into Redshift. Option B is wrong because Kinesis Data Streams requires a custom producer to capture Oracle changes and does not provide native CDC from Oracle databases. Option C is wrong because AWS Glue with JDBC is batch-oriented and does not support real-time change data capture natively. Option D is wrong because AWS Lambda can process events but is not designed for continuous, low-latency CDC from a database and would require polling or triggers.
What should I do if I get this DEA-C01 question wrong?
Review ACL processing order, placement rules (standard near destination, extended near source), and inbound vs outbound direction. Study wildcard masks and implicit deny. Then practise related DEA-C01 ACL questions on filtering logic and placement.
What is the key concept behind this question?
Standard ACLs match source addresses.
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Last reviewed: Jun 20, 2026
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