The correct approach is to configure DMS with ongoing replication using change data capture (CDC). This is the right choice because CDC captures incremental changes from the Oracle source database—using Oracle LogMiner or binary logs—and applies them to Amazon Redshift in near real-time, ensuring the target stays synchronized with minimal latency after the initial full load. On the AWS Certified Data Engineer Associate DEA-C01 exam, this scenario tests your understanding of DMS migration patterns beyond a one-time load; a common trap is assuming a scheduled batch job or manual refresh suffices, but the question explicitly demands ongoing consistency with low latency, which only CDC provides. Remember: if the source keeps changing, you need CDC to catch every change. A helpful memory tip is to think “CDC = Continuous Data Catch-up,” reinforcing that it’s the only method that tracks row-level modifications as they happen.
DEA-C01 Data Operations and Support Practice Question
This DEA-C01 practice question tests your understanding of data operations and support. 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 DMS to migrate data from an on-premises Oracle database to Amazon Redshift. The migration is successful, but after a few days, data in Redshift becomes inconsistent with the source due to ongoing changes. The company needs to keep Redshift synchronized with minimal latency. Which approach should the data engineer use?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Configure DMS with ongoing replication using change data capture (CDC).
AWS DMS supports ongoing replication using change data capture (CDC), which captures incremental changes from the Oracle source (via Oracle LogMiner or binary logs) and applies them to Amazon Redshift in near real-time. This approach ensures that Redshift remains synchronized with the source database with minimal latency, meeting the requirement for ongoing consistency after the initial full load.
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.
✓
Configure DMS with ongoing replication using change data capture (CDC).
Why this is correct
CDC captures changes continuously and applies them to Redshift.
Related concept
Read the scenario before looking for a memorised answer.
✗
Use Amazon Redshift COPY with S3 staging and AWS Lambda triggers.
Why it's wrong here
This approach requires custom coding and does not capture all changes.
✗
Schedule a full DMS load every night.
Why it's wrong here
Full loads are time-consuming and do not provide low-latency sync.
✗
Set up Amazon Redshift Spectrum to query the Oracle database directly.
Why it's wrong here
Spectrum queries external data in S3, not live databases.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates may confuse Amazon Redshift Spectrum's federated querying capability with actual data replication, or assume that nightly batch loads (Option C) are sufficient for 'minimal latency' requirements, when DMS CDC is the only option that provides continuous, low-latency synchronization.
Detailed technical explanation
How to think about this question
DMS CDC for Oracle uses Oracle's LogMiner or Oracle GoldenGate to read redo logs and capture committed transactions, which are then transformed and applied to Redshift via batch-optimized writes. A subtle behavior is that DMS CDC requires the source Oracle database to have supplemental logging enabled for all columns to ensure complete change capture, and it uses a transaction consistency model that may introduce a few seconds of lag depending on log volume and network throughput.
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.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Data Operations and Support — This question tests Data Operations and Support — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Configure DMS with ongoing replication using change data capture (CDC). — AWS DMS supports ongoing replication using change data capture (CDC), which captures incremental changes from the Oracle source (via Oracle LogMiner or binary logs) and applies them to Amazon Redshift in near real-time. This approach ensures that Redshift remains synchronized with the source database with minimal latency, meeting the requirement for ongoing consistency after the initial full load.
What should I do if I get this DEA-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
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These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. A company uses AWS DMS to migrate data from an on-premises Oracle database to Amazon Aurora MySQL. After the migration, the data in Aurora is inconsistent with the source. The engineer needs to ensure ongoing replication with minimal downtime. Which solution should the engineer implement?
medium
A.Use AWS Schema Conversion Tool (SCT) to convert the schema
B.Export the data from Oracle and import into Aurora using mysqldump
✓ C.Configure a DMS task with change data capture (CDC)
D.Perform a full load migration again
Why C: Option B is correct because using DMS with change data capture (CDC) captures ongoing changes and replicates them with minimal downtime. Option A is wrong because full load only captures a snapshot. Option C is wrong because AWS Schema Conversion Tool does not handle data replication. Option D is wrong because exporting and importing does not provide ongoing replication.
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Question Discussion
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