PAS-C01 Design of SAP Workloads on AWS Practice Question
A company is running SAP Business Suite on AWS using an Oracle database. They need to migrate the Oracle database to SAP HANA as part of an SAP S/4HANA conversion. The current Oracle database size is 5 TB and runs on an r5.8xlarge instance. The target HANA database will run on an r5.24xlarge instance. The company wants to minimize downtime. What is the best approach to migrate the data?
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 SAP Software Update Manager (SUM) with the Database Migration Option (DMO) to migrate and upgrade in one step.
SAP provides the Software Update Manager (SUM) with DMO (Database Migration Option) to perform the migration and upgrade in one step, minimizing downtime. Option A (native Oracle export/import) is time-consuming. Option B (AWS DMS) is not fully supported for SAP HANA as target. Option C (SAP Landscape Transformation) is for data replication but not for a one-step migration with upgrade. Option D is correct.
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 Database Migration Service (DMS) to continuously replicate data from Oracle to HANA, then switch over.
Why it's wrong here
DMS does not fully support HANA as target for SAP migrations.
- ✗
Use SAP Landscape Transformation (SLT) to replicate data in real-time from Oracle to HANA.
Why it's wrong here
SLT is for ongoing replication, not a one-time migration with upgrade.
- ✗
Use Oracle Data Pump to export the database and import into HANA using SAP HANA studio.
Why it's wrong here
Data Pump export/import is slow and causes extended downtime.
- ✓
Use SAP Software Update Manager (SUM) with the Database Migration Option (DMO) to migrate and upgrade in one step.
Why this is correct
SUM with DMO performs the migration and upgrade in a single process, minimizing downtime.
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