Transformations Guide
Transformations let you clean, rename, or enrich data during sync.
✨ What Can You Transform?
- Rename Fields
- Change Data Types
- Format Dates
- Hide Sensitive Data
- Apply Formulas
✨ Example Use Cases
| Transformation | Example |
|---|---|
| Rename Field | AccountNumber ➡️ account_id |
| Format Date | CreatedDate ➡️ YYYY-MM-DD |
| Mask Data | Replace email with ****@domain.com |
| Default Values | If Industry is empty, set to Other |
✨ How to Configure
- In the Map Schema step, locate the Transformation column.
- Select the transformation type.
- Provide parameters (e.g., new field name).
- Save mapping.
✨ Tips
- Keep transformations simple during initial sync.
- Test with small datasets first.
- Document any logic applied.
For more detail, refer to the Schema Mapping Overview.