SAP SuccessFactors · HCM · Master data
Migrate employee records into SuccessFactors Employee Central, covering basic user information, biographical and personal data, national identifiers, addresses and the dependencies that gate the load.
The employee in Employee Central is not one record. It is a set of related entities — basic user information, person, biographical information, personal information, national ID, addresses, contacts — loaded in a defined sequence through separate import templates.
Person ID External is the key decision on this object. It ties every subsequent entity together and determines whether history stays traceable back to the legacy system, so it is settled before any template is built.
Scope is agreed in discovery; this is the shape of the object.
| Data area | Typical information |
|---|---|
| Basic user information | User ID, Person ID External, username, status, email |
| Person | The person container that employment and biographical data attach to |
| Biographical information | Date of birth, country of birth, gender |
| Personal information | Name, marital status, nationality — effective-dated |
| National ID | Identifier, card type, country, primary flag |
| Addresses | Home and mailing addresses, country-specific formats, effective-dated |
| Contacts | Emergency contacts and dependants where in scope |
Dependency drives load sequence: a child cannot exist before its parent.
Confirm each of these before the first migration cycle.
Production-proven means we have delivered this object from that source. Supported and custom-mapping describe capability, not delivery history.
Object-level equivalence. Field-level mapping is produced per engagement.
| Source system | Source entity | Target object |
|---|---|---|
| JD Edwards | Address Book (F0101) + Employee Master (F060116) | Basic user + Person + Biographical |
| PeopleSoft | PERSONAL_DATA + PERS_NID | Person + Biographical + National ID |
| SAP HCM | Infotypes 0002 / 0006 / 0021 | Biographical + Address + Dependants |
Import Employee Data — CSV templates per entity
Full purge for the initial load, incremental for subsequent cycles
OData API for post-go-live maintenance rather than bulk migration
Duplicates break every dependent entity.
Which differ by legal entity country.
Gender, marital status, nationality and ID card type all resolve to configured values.
Date of birth is plausible and precedes hire date.
Per the country-specific format.
Where the country enforces one.
What has to exist before this object can load.
What actually fails on this object, and why.
Counts alone rarely prove this object migrated correctly.
Employee count: source population in scope vs loaded, by legal entity
Entity coverage per person: biographical, personal, national ID and address counts
Country-specific completeness for populations with mandatory identifiers
Key field comparison on a sample: date of birth, name components, national ID
Rejected records categorised by entity and reason
Extraction, mapping, transformation, validation preparation and target load generation.
Explore DataMove →Preserves source, prepared and target states for reconciliation, lineage and audit evidence.
Explore DataVault →Migration progress, data quality, exceptions and readiness across cycles.
Explore DataLens →Source-specific guidance for moving this object.
Published case studies whose scope included employee.
Tell us your source application, target system, object scope, volume and migration timeline. We can discuss the recommended migration approach and relevant Syntra ETL project experience.