Field Mappings
Use Field Mappings when you want to to re-use the same field mapping between external Data Source and a Data Schema in your app.
Examples of scenarios when Field Mappings are useful are:
  • Having separate “Create X” and “Update X” flows without need for your user to configure field mapping twice.
  • Bi-directional data sync: using the same (but reversed) field mapping for inbound and outbound integration flows.

Data Source

Pick a Data Source you want to map fields from/to. If it as a Unified Data Model associated, you will be able to use it to create a default field mapping.

App Data Schema

You can choose an App Data Collection or specify a Data Schema right here. If App Data Collection with user-specific fields is used, the schema used in integrations may differ from user to user. The up-to-date schema will be pulled every time the user opens the field mapping configuration.

Direction

You can create mapping that works in one direction or both directions. Depending on the direction, this mapping will be available in "import" integrations (list / find / find by id flow nodes and data-related triggers) or "export" integrations (create / update flow nodes).

Default Mapping

If both sides of the mapping have a schema known, you will be able to specify the default mapping.
When applied to a specific user and specific connection, the default mapping will be translated into specific Data Schemas used on your app side and in the external application automatically. It will be used as default value that your users can change.

Field Mapping Instances

We will create a new instance of field mapping for each pair of external and app-side schemas. For example:
  • Each instance of Data Source will have its own mapping instance.
  • Each instance of App Data Collection will have its own mapping instance.
Generally, this makes Field Mappings work just like you would expect them to work.
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Outline
Data Source
App Data Schema
Direction
Default Mapping
Field Mapping Instances