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ETL Sage US in Oracle Data Integrator

This article shows how to transfer Sage US data into a data warehouse using Oracle Data Integrator.

Leverage existing skills by using the JDBC standard to read and write to Sage US: Through drop-in integration into ETL tools like Oracle Data Integrator (ODI), the CData JDBC Driver for Sage US connects real-time Sage US data to your data warehouse, business intelligence, and Big Data technologies.

JDBC connectivity enables you to work with Sage US just as you would any other database in ODI. As with an RDBMS, you can use the driver to connect directly to the Sage US APIs in real time instead of working with flat files.

This article walks through a JDBC-based ETL -- Sage US to Oracle. After reverse engineering a data model of Sage US entities, you will create a mapping and select a data loading strategy -- since the driver supports SQL-92, this last step can easily be accomplished by selecting the built-in SQL to SQL Loading Knowledge Module.

Install the Driver

To install the driver, copy the driver JAR and .lic file, located in the installation folder, into the ODI userlib directory:

On Unix: ~/.odi/oracledi/userlib On Windows: %APPDATA%\Roaming\odi\oracledi\userlib

Restart ODI to complete the installation.

Reverse Engineer a Model

Reverse engineering the model retrieves metadata about the driver's relational view of Sage US data. After reverse engineering, you can query real-time Sage US data and create mappings based on Sage US tables.

  1. In ODI, connect to your repository and click New -> Model and Topology Objects.
  2. On the Model screen of the resulting dialog, enter the following information:
    • Name: Enter Sage50US.
    • Technology: Select Generic SQL (for ODI Version 12.2+, select Microsoft SQL Server).
    • Logical Schema: Enter Sage50US.
    • Context: Select Global.
  3. On the Data Server screen of the resulting dialog, enter the following information:
    • Name: Enter Sage50US.
    • Driver List: Select Oracle JDBC Driver.
    • Driver: Enter cdata.jdbc.sage50us.Sage50USDriver
    • URL: Enter the JDBC URL containing the connection string.

      The Application Id and Company Name connection string options are required to connect to Sage as a data source. You can obtain an Application Id by contacting Sage directly to request access to the Sage 50 SDK.

      Sage must be installed on the machine. The Sage.Peachtree.API.dll and Sage.Peachtree.API.Resolver.dll assemblies are required. These assemblies are installed with Sage in C:\Program Files\Sage\Peachtree\API\. Additionally, the Sage SDK requires .NET Framework 4.0 and is only compatible with 32-bit applications. To use the Sage SDK in Visual Studio, set the Platform Target property to "x86" in Project -> Properties -> Build.

      You must authorize the application to access company data: To authorize your application to access Sage, restart the Sage application, open the company you want to access, and connect with your application. You will then be prompted to set access permissions for the application in the resulting dialog.

      While the compiled executable will require authorization only once, during development you may need to follow this process to reauthorize a new build. To avoid restarting the Sage application when developing with Visual Studio, click Build -> Configuration Manager and uncheck "Build" for your project.

      Built-in Connection String Designer

      For assistance in constructing the JDBC URL, use the connection string designer built into the Sage US JDBC Driver. Either double-click the JAR file or execute the jar file from the command-line.

      java -jar cdata.jdbc.sage50us.jar

      Fill in the connection properties and copy the connection string to the clipboard.

      Below is a typical connection string:

      jdbc:sage50us:ApplicationId=8dfafu4V4ODmh1fM0xx;CompanyName=Bellwether Garden Supply - Premium;
  4. On the Physical Schema screen, enter the following information:
    • Schema (Schema): Enter Sage50US.
    • Schema (Work Schema): Enter Sage50US.
  5. In the opened model click Reverse Engineer to retrieve the metadata for Sage US tables.

Edit and Save Sage US Data

After reverse engineering you can now work with Sage US data in ODI. To edit and save Sage US data, expand the Models accordion in the Designer navigator, right-click a table, and click Data. Click Refresh to pick up any changes to the data. Click Save Changes when you are finished making changes.

Create an ETL Project

Follow the steps below to create an ETL from Sage US. You will load Customer entities into the sample data warehouse included in the ODI Getting Started VM.

  1. Open SQL Developer and connect to your Oracle database. Right-click the node for your database in the Connections pane and click new SQL Worksheet.

    Alternatively you can use SQLPlus. From a command prompt enter the following:

    sqlplus / as sysdba
  2. Enter the following query to create a new target table in the sample data warehouse, which is in the ODI_DEMO schema. The following query defines a few columns that match the Customer table in Sage US: CREATE TABLE ODI_DEMO.TRG_CUSTOMER (LASTINVOICEAMOUNT NUMBER(20,0),Name VARCHAR2(255));
  3. In ODI expand the Models accordion in the Designer navigator and double-click the Sales Administration node in the ODI_DEMO folder. The model is opened in the Model Editor.
  4. Click Reverse Engineer. The TRG_CUSTOMER table is added to the model.
  5. Right-click the Mappings node in your project and click New Mapping. Enter a name for the mapping and clear the Create Empty Dataset option. The Mapping Editor is displayed.
  6. Drag the TRG_CUSTOMER table from the Sales Administration model onto the mapping.
  7. Drag the Customer table from the Sage US model onto the mapping.
  8. Click the source connector point and drag to the target connector point. The Attribute Matching dialog is displayed. For this example, use the default options. The target expressions are then displayed in the properties for the target columns.
  9. Open the Physical tab of the Mapping Editor and click CUSTOMER_AP in TARGET_GROUP.
  10. In the CUSTOMER_AP properties, select LKM SQL to SQL (Built-In) on the Loading Knowledge Module tab.

You can then run the mapping to load Sage US data into Oracle.