The scenario: There are multiple databases which store datasets for the same feature types, but table names and column names are vary for each. The mission is to migrate the multiple databases to new multiple datasets which have common schema (i.e. common feature type names, common attribute names).
Other than data tables, every database has two mapping tables - one defines the mapping rule between table names and destination common feature type names, another defines the mapping rule between column names and destination common attribute names for each feature type. Fortunately, schema of the mapping tables are common to every database.
If it was possible to set user parameters or feature attributes to the SchemaMapper's Dataset parameters (including database connection parameters), a workspace containing a SchemaMapper could do the task with batch processing. However, the Dataset parameters cannot be parameterized in the current SchemaMapper, so you need to set the connection parameters manually for each database.
In fact, I resolved this with a workflow containing Python scripts which perform schema mapping for each database based on the mapping tables, but I thought it would be easier if the SchamaMapper's Dataset parameters could be parameterized.
