Build Salesforce Data Cloud-Connected ETL Processes in Google Data Fusion

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

Upload the CData JDBC Driver for Salesforce Data Cloud to Google Data Fusion

Upload the CData JDBC Driver for Salesforce Data Cloud to your Google Data Fusion instance to work with live Salesforce Data Cloud 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 driver-version.jar. For example: cdatasalesforcedatacloud-2020.jar

1. Open your Google Data Fusion instance
2. Click the to add an entity and upload a driver 👁 Image
   
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.salesforcedatacloud) and make note of the name
   • Class name: Set the JDBC class name: (cdata.jdbc.salesforcedatacloud.SalesforceDataCloudDriver)
   👁 Configuring the driver (Salesforce is shown.)
   
5. Click "Finish"

Connect to Salesforce Data Cloud Data in Google Data Fusion

With the JDBC Driver uploaded, you are ready to work with live Salesforce Data Cloud 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 👁 Adding a database source
   
3. Click "Properties" on the Database source to edit the properties

   NOTE: To use the JDBC Driver in Google Data Fusion, you will need a license (full or trial) and a Runtime Key (RTK). For more information on obtaining this license (or a trial), contact our sales team.

   • Set the Label
   • Set Reference Name to a value for any future references (i.e.: cdata-salesforcedatacloud)
   • Set Plugin Type to "jdbc"
   • Set Connection String to the JDBC URL for Salesforce Data Cloud. For example:
     
     jdbc:salesforcedatacloud:RTK=5246...;InitiateOAuth=GETANDREFRESH;

     Salesforce Data Cloud supports authentication via the OAuth standard.

     OAuth

     Set to OAuth.

     Desktop Applications

     CData provides an embedded OAuth application that simplifies authentication at the desktop.

     You can also authenticate from the desktop via a custom OAuth application, which you configure and register at the Salesforce Data Cloud console. For further information, see Creating a Custom OAuth App in the Help documentation.

     Before you connect, set these properties:

     • : GETANDREFRESH. You can use to avoid repeating the OAuth exchange and manually setting the .
     • (custom applications only): The Client ID assigned when you registered your custom OAuth application.
     • (custom applications only): The Client Secret assigned when you registered your custom OAuth application.

     When you connect, the driver opens Salesforce Data Cloud's OAuth endpoint in your default browser. Log in and grant permissions to the application.

     The driver then completes the OAuth process as follows:

     • Extracts the access token from the callback URL.
     • Obtains a new access token when the old one expires.
     • Saves OAuth values in so that they persist across connections.

     For other OAuth methods, including Web Applications and Headless Machines, refer to the Help documentation.

     Built-in Connection String Designer

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

      java -jar cdata.jdbc.salesforcedatacloud.jar
      

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

     👁 Using the built-in connection string designer to generate a JDBC URL (Salesforce is shown.)
     
   • Set Import Query to a SQL query that will extract the data you want from Salesforce Data Cloud, i.e.:
     SELECT * FROM Account
   👁 Configuring the database source
   
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 salesforcedatacloud-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 Salesforce Data Cloud data into
   👁 Configuring the BigQuery sink
   

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

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