Preparing the ETL catalog

The extract, transform, and load (ETL) catalog contains the fact tables and dimension tables that define how the data is extracted, transformed, and delivered to the data warehouse. When you prepare the ETL catalog for the ETL process, you specify the access information needed to access the database of the data warehouse and you restore the sample catalog .
Before you begin
Ensure that you have created an empty database to store the ETL catalog. For information on how to create databases, see documentation for the database application that you use.
About this task
To create an ETL catalog:
  1. Start IBM® Cognos® Data Manager.
  2. Click File > New catalog.
  3. Type a name, business name, and description for the catalog and click Next.

    The Business name and Description fields are optional.

  4. Specify the details of the empty database that you created for the catalog and click Finish.

    You have created an empty catalog.

    The IBM Rational® Insight installation package contains a sample ETL catalog that you can use to test the package. In the next optional steps, you can restore the sample ETL catalog to IBM Cognos Data Manager. Before testing the installation, verify that all connections specify the data sources that you prepared.

  5. Optional: Click File > Restore catalog and select the sample ETL catalog. The default directory of the catalog file is [INSTALLDIR]/datamgr/RationaInsight_catalog.
  6. Optional: Expand the ETL catalog node, and expand the Library > Connections node. The data source connections are listed.
  7. Optional: To see or change the connection properties or to test a connection, double-click the connection.
    • You can change the data source name.
    • You can test a data source connection by clicking Test Connection.
    • You can change the connection properties of the data source to specify for the database the data warehouse that you prepared for Rational Insight.
      Tip: For details about preparing the data warehouse, see the Preparing the data warehouse topic.

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