Table of Contents

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  1. Preface
  2. Informatica Developer
  3. The Model Repository
  4. Searches in Informatica Developer
  5. Connections
  6. Physical Data Objects
  7. Flat File Data Objects
  8. Logical View of Data
  9. Viewing Data
  10. Application Deployment
  11. Object Import and Export
  12. Data Type Reference
  13. Keyboard Shortcuts
  14. Connection Properties

Developer Tool Guide

Developer Tool Guide

Informatica Data Services

Informatica Data Services

Data services are a collection of reusable operations that you can run to access and transform data.
Use the data services capabilities in the Developer tool to complete the following tasks:
  • 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.
  • Export mappings to PowerCenter. You can export mappings to PowerCenter to reuse the metadata for physical data integration or to create web services.
    The Developer tool does not include options to import from and export to PowerCenter.
  • 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.

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