DBS-C01 Deployment and Migration Practice Question
A company is planning to migrate a 5 TB Oracle data warehouse to Amazon Redshift. The migration must be completed within a 2-day maintenance window. The source database is heavily normalized and uses complex joins. Which strategy is most appropriate?
⚠ Common exam trap
Watch out — candidates often assume DMS alone can handle schema conversion, but DMS is a data migration service, not a schema transformation tool; SCT is required for converting complex Oracle schemas to Redshift-optimized formats.
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 SCT to convert the Oracle schema to Redshift-compatible format, then use AWS DMS to load the data.
AWS Schema Conversion Tool (SCT) is specifically designed to convert Oracle schemas (including heavily normalized structures with complex joins) into Amazon Redshift-compatible format, which is essential for a data warehouse migration. AWS DMS then efficiently loads the converted schema and data into Redshift within the 2-day window, as it can handle large volumes with full load and ongoing replication if needed.
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 AWS DMS to directly migrate data to Redshift with full load and ongoing replication.
Why it's wrong here
DMS can load data, but schema conversion from Oracle to Redshift is needed first.
- ✗
Export data to flat files, use S3 Transfer Acceleration to upload to S3, then COPY into Redshift.
Why it's wrong here
This approach does not convert the schema; Redshift requires a columnar schema.
- ✓
Use AWS SCT to convert the Oracle schema to Redshift-compatible format, then use AWS DMS to load the data.
Why this is correct
AWS SCT converts Oracle’s normalised schema and complex joins into Redshift’s columnar, denormalised format, while AWS DMS performs the continuous 5 TB load within the 2-day window using full-load plus change data capture, satisfying the tight migration deadline.
- ✗
Use AWS Glue to crawl the Oracle schema and create Redshift tables, then run a Glue ETL job to load data.
Why it's wrong here
Glue can do ETL but is not optimized for large-scale migration with schema conversion like SCT.
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