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Build Sage US-Connected ETL Processes in Google Data Fusion

Load the CData JDBC Driver into Google Data Fusion and create ETL processes with access live Sage US data.

Google Data Fusion allows users to perform self-service data integration to consolidate disparate data. Uploading the CData JDBC Driver for Sage US enables users to access live Sage US data from within their Google Data Fusion pipelines. While the CData JDBC Driver enables piping Sage US data to any data source natively supported in Google Data Fusion, this article walks through piping data from Sage US to Google BigQuery,

Upload the CData JDBC Driver for Sage US to Google Data Fusion

Upload the CData JDBC Driver for Sage US to your Google Data Fusion instance to work with live Sage US data. Due to the naming restrictions for JDBC drivers in Google Data Fusion, create a copy or rename the JAR file to match the following format -.jar. For example: cdata.jdbc.sage50us-2019.jar

  1. Open your Google Data Fusion instance
  2. Click the to add an entity and upload a driver
  3. On the "Upload driver" tab, drag or browse to the renamed JAR file.
  4. On the "Driver configuration" tab:
    • Name: Create a name for the driver (cdata.jdbc.sage50us) and make note of the name
    • Class name: Set the JDBC class name: (cdata.jdbc.sage50us.Sage50USDriver)
  5. Click "Finish"

Connect to Sage US Data in Google Data Fusion

With the JDBC Driver uploaded, you are ready to work with live Sage US data in Google Data Fusion Pipelines.

  1. Navigate to the Pipeline Studio to create a new Pipeline
  2. From the "Source" options, click "Database" to add a source for the JDBC Driver
  3. Click "Properties" on the Database source to edit the properties
    • Set the Label
    • Set Reference Name to a value for any future references (i.e.: cdata-sage50us)
    • Set Plugin Type to "jdbc"
    • Set Connection String to the JDBC URL for Sage US. For example:

      jdbc:sage50us:RTK=5246...;ApplicationId=8dfafu4V4ODmh1fM0xx;CompanyName=Bellwether Garden Supply - Premium;

      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.

      To use the JDBC Driver in Google Data Fusion, you will need to set the RTK property in the JDBC URL. You can view the licensing file included in the installation for information on how to set this property.

      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.

    • Set Import Query to a SQL query that will extract the data you want from Sage US, i.e.:
      SELECT * FROM Customer
  4. From the "Sink" tab, click to add a destination sink (we use Google BigQuery in this example)
  5. Click "Properties" on the BigQuery sink to edit the properties
    • Set the Label
    • Set Reference Name to a value like sage50us-bigquery
    • Set Project ID to a specific Google BigQuery Project ID (or leave as the default, "auto-detect")
    • Set Dataset to a specific Google BigQuery dataset
    • Set Table to the name of the table you wish to insert Sage US data into

With the Source and Sink configured, you are ready to pipe Sage US data into Google BigQuery. Save and deploy the pipeline. When you run the pipeline, Google Data Fusion will request live data from Sage US and import it into Google BigQuery.

While this is a simple pipeline, you can create more complex Sage US pipelines with transforms, analytics, conditions, and more. Download a free, 30-day trial of the CData JDBC Driver for Sage US and start working with your live Sage US data in Google Data Fusion today.