Field Mapping allows users to create logical connections between metadata content in Grooper and an external storage platform.
For example, field mappings can be created between data elements in a data model in Grooper and corresponding metadata fields in an external content management system. A Data Field capturing an invoice document's invoice number could be mapped to a field in the content management system named "Invoice Number". After those data fields are extracted from a document set, when the documents are exported their information will populate the mapped fields in the content management system.
Field mappings can be used for both import and export operations. Document metadata from an external storage platform can be imported via field mappings as well as exported.
Grooper Version 2.72 introduces simplified field mappings. Fields can now be mapped as they are defined at the root of the Data Model.
|If your Data Model looks like the one below with fields in several different sections...
||...when you go to map them to (or from) a CMIS repository, the dropdown list will be structured like your Data Model, from top to bottom with each heading listed before the field. This makes it much easier to find which field you're looking for.
Beginning in 2.80, administrators now have the ability to add expressions to mapped fields on import and export.
When setting up a Database Export activity, new options are exposed on the "column mappings" property.
These expressions use the same syntax and expose the same objects and variables as calculate and validate expressions. This feature supplements (rather than replaces) the old column mappings. Mapped objects now have an "Expression" property, which defaults to an unaltered output of the mapped Grooper Data Field.
The expression editor window also supports IntelliSense, which users should use as an aide when building calculate expressions.
In situations where export databases expect data that is in a different format than what has been extracted by Grooper, field mapping can be used to transform that data into the appropriate type.
- Zero-padded fields
If Grooper extracts an Employee ID as
123456, but the database is expecting a value of nine characters to be stored (with zero padding for shorter IDs), you can set the mapping on export to send
- Instances in which first, middle, and last names need to be in a specific order
If Grooper extracts
Chris P. Bacon (first, middle, last), but the database is expecting
Bacon, Chris P., you can set that transformation on export using field mapping expressions.
When data about the Grooper process itself needs to be exported (user, batch name, statistics, machine name, etc.), these can be mapped to their corresponding database columns using expression-based mapping.