Which sequence correctly describes migrating data from legacy talent management systems to Oracle HCM Cloud?

Which sequence correctly describes migrating data from legacy talent management systems to Oracle HCM Cloud?

• A. Rebuild data manually in the new system.
• B. Export, import, validate, and go live with no sandbox testing.
• C. Data mapping, cleanse, transform, validate, test migration in sandbox, run cutover plan, verify data integrity.
• D. Copy data from legacy to Oracle HCM Cloud and run basic checks.

Answer: (C)

The key idea is to follow a structured data migration lifecycle rather than moving data haphazardly. Start with data mapping to align each legacy field with the corresponding Oracle HCM Cloud field, setting rules for formats and relationships. Then cleanse the data to remove duplicates, fix inaccuracies, and standardize values so they fit the target schema. Transform the data into the exact structures and types required by HCM Cloud. After that, validate the transformed data to catch issues early, ensuring accuracy and completeness. Next, test the migration in a sandbox environment to verify that the data transfers correctly, interfaces behave as expected, and business processes function without touching production data. Once testing is successful, execute the cutover plan to coordinate the go-live activities, timing, and rollback options if needed. Finally, verify data integrity in production after migration and perform reconciliation to confirm that counts and key records are accurate. This approach minimizes risk and ensures a clean, reliable transition.

The key idea is to follow a structured data migration lifecycle rather than moving data haphazardly. Start with data mapping to align each legacy field with the corresponding Oracle HCM Cloud field, setting rules for formats and relationships. Then cleanse the data to remove duplicates, fix inaccuracies, and standardize values so they fit the target schema. Transform the data into the exact structures and types required by HCM Cloud. After that, validate the transformed data to catch issues early, ensuring accuracy and completeness. Next, test the migration in a sandbox environment to verify that the data transfers correctly, interfaces behave as expected, and business processes function without touching production data. Once testing is successful, execute the cutover plan to coordinate the go-live activities, timing, and rollback options if needed. Finally, verify data integrity in production after migration and perform reconciliation to confirm that counts and key records are accurate. This approach minimizes risk and ensures a clean, reliable transition.