Define logical views of data. A logical view of data describes the structure and use of data in an enterprise. You can create a logical data object model that shows the types of data your enterprise uses and how that data is structured.

Map logical models to data sources or targets. Create a mapping that links objects in a logical model to data sources or targets. You can link data from multiple, disparate sources to create a single view of the data. You can also load data that conforms to a model to multiple, disparate targets.

Create virtual views of data. You can deploy a virtual federated database to a Data Integration Service. End users can run SQL queries against the virtual data without affecting the actual source data.

Provide access to data integration functionality through a web service interface. You can deploy a web service to a Data Integration Service. End users send requests to the web service and receive responses through SOAP messages.

Use the Developer tool or infacmd to import mappings from PowerCenter or export mappings to PowerCenter to reuse the metadata.

To import data from PowerCenter into the Model Repository, complete the following tasks:

Export PowerCenter objects to a file using the PowerCenter Client or with the following command:
pmrep ExportObject
Convert the export file to a Model repository file using the following command:
infacmd ipc importFromPC
Import the objects using the Developer tool or with the following command:
infacmd tools importObjects

To export data from the Model repository into the PowerCenter repository, complete the following tasks:

Export Model Repository objects to a file using the Developer tool or with the following command:
infacmd tools ExportObjects
Or, you can directly run
infacmd ipc ExportToPC
to export.
Convert the export file to a PowerCenter file using the following command:
infacmd ipc ExporttoPC
Import the objects using the PowerCenter or with the following command:
pmrep importObjects

Create and deploy mappings that domain users can run from the command line.

Profile data. If you use the Profiling option, profile data to reveal the content and structure of data. Profiling is a key step in any data project, as it can identify strengths and weaknesses in data and help you define a project plan.