01 - Model
Make the destination schema explicit.
Document the fields, objects, relationships, and constraints that matter to your platform before customers upload their source files.
Schema mapping
Schema mapping that gives every customer file a destination.
Aformity helps teams connect source columns, legacy exports, and customer-specific fields to the exact objects and fields your platform expects.
Workflow
How Aformity turns messy files into a repeatable launch motion.
02 - Match
Map source fields without relying on guesswork.
Connect customer columns to destination fields, preserve relationships, and decide which source data should be transformed, archived, or excluded.
03 - Transform
Apply rules where field names are not enough.
Use plugins to normalize values, split or merge columns, convert data types, and reshape records into the destination system's expected format.
Direct answer
What is schema mapping in data migration?
Schema mapping is the process of matching fields from a source system or customer file to the fields and objects in the destination platform. Good schema mapping also handles relationships, required fields, allowed values, transformations, and fields that should not be imported.
Before / after
Replace fragile import prep with an auditable workflow.
Source fields
Columns are renamed by hand in spreadsheets.
Mappings connect each source column to an explicit destination field.
Relationships
Parent-child links are checked late in the import process.
Relationship rules are part of the mapping workflow from the start.
Reusable logic
Each customer mapping starts from a blank spreadsheet.
Successful mappings become templates for similar customers.
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