Data Mapping Definition
Data mapping is the process of defining how fields from one system or data source correspond to fields in another. It is the translation layer that makes it possible to move or sync data between systems without losing meaning or structure.
When is data mapping needed?
Any time data moves between systems with different structures, mapping is required. Common scenarios include connecting a PIM to an ecommerce platform, importing supplier data into a product catalog, or syncing product records with an ERP. Without a defined map, fields land in the wrong place, values get misread, or data is dropped entirely.
What does a data map define?
A data map specifies which source field connects to which destination field, how values should be transformed in transit (for example, converting a unit of measure or reformatting a date), and what happens when a source field has no match in the destination. In practice, mapping rules are configured in an integration tool, an ETL pipeline, or directly inside a PIM's import settings.
Why does it matter for product data?
Suppliers rarely send product data in the exact format a retailer or distributor needs. Attribute names differ, classification codes vary, and units may not align. Maintaining clear, documented mapping rules reduces import errors, speeds up product onboarding, and makes it easier to add new suppliers or channels without rebuilding integrations from scratch.
