Data mapping defines how information in a source corresponds to fields in a destination. It should preserve meaning, not merely connect columns with similar names.
Review the field meaning
In a candidate spreadsheet, a column called location might describe residence, preferred market, or a former employer's address. Establish which meaning applies before selecting the destination. Check formatting and representative rows so a mapping that works for one part of the file does not misinterpret another.
InferOwl spreadsheet import includes column-mapping review. Inspect names, contact details, duplicate warnings, and invalid values before committing ready rows. A successful mapping still depends on accurate source information.
Plan ongoing ownership
For an integration, identify which system is authoritative for each shared field and how conflicts should be resolved. Decide who can approve changes to the mapping when the source format or workflow changes. Use the import guide for batch review and the connection-methods reference for integration responsibilities. Check saved destination records before treating the exchange as complete.