DBS-C01 Deployment and Migration Practice Question
A company is migrating a 500 GB Oracle database to Amazon RDS for Oracle. They need to validate the migration and ensure data consistency. Which TWO methods should they use?
⚠ Common exam trap
Candidates often choose Option C (random SELECT queries) thinking it is sufficient for validation, but the exam expects you to recognize that sampling is not statistically reliable for a 500 GB database and that AWS DMS provides a purpose-built, automated validation feature.
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
✓
Use AWS DMS data validation feature.
AWS DMS data validation (Option B) is a built-in feature that automatically compares source and target records by computing checksums on each row, ensuring end-to-end data consistency without manual effort. Comparing row counts and checksums (Option D) is a standard manual validation technique that provides a reliable, independent verification of data completeness and integrity. Together, these two methods cover both automated and manual validation, which is critical for a 500 GB migration where manual inspection of every row is impractical.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use Amazon S3 inventory reports on the exported data.
Why it's wrong here
S3 inventory is for object storage, not database consistency.
- ✓
Use AWS DMS data validation feature.
Why this is correct
DMS validation compares source and target data automatically.
- ✗
Run random SELECT queries on a subset of tables.
Why it's wrong here
Random sampling does not guarantee full consistency.
- ✓
Compare row counts and checksums on both databases.
Why this is correct
Row counts and checksums provide a reliable comparison.
- ✗
Use Amazon CloudWatch Logs to compare database logs.
Why it's wrong here
CloudWatch logs do not provide data validation.
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