Data Mapping
Data mapping is the process of matching and transforming data fields from one system or format to the corresponding fields in another system or format.
What is Data Mapping?
Data mapping is the process of establishing relationships between data fields in a source system and the corresponding fields in a target system. It is a fundamental step in data integration, migration, and synchronization projects.
In product information management, data mapping is used when importing product data from a supplier spreadsheet, an ERP system, or a legacy catalog into a PIM — ensuring that each supplier's "Product Name" field maps correctly to the PIM's "Title" field, for example.
Types of Data Mapping
- Manual mapping — a human manually defines field relationships
- Semi-automated mapping — software suggests matches based on field names or data patterns
- Transformation mapping — data is not just moved but converted (e.g., unit conversion, date format changes)
- Schema mapping — entire data models or schemas are mapped to each other
Why Data Mapping is Important
Poor data mapping leads to corrupted or misaligned product data, which causes incorrect listings, broken integrations, and poor customer experiences. A well-defined mapping process ensures that data flows accurately between systems.
Frequently Asked Questions
What is the difference between data mapping and data transformation?
Data mapping defines which fields correspond to each other across systems. Data transformation changes the format or structure of the data during the transfer. Many integrations require both.
How does Apimio handle data mapping?
Apimio provides flexible import tools that allow teams to map incoming supplier or ERP data fields to the correct PIM attributes during the import process, with support for custom transformation rules.