Build Salesforce-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 enables users to access live Salesforce data from within their Google Data Fusion pipelines. While the CData JDBC Driver enables piping Salesforce data to any data source natively supported in Google Data Fusion, this article explains how to pipe data from Salesforce to Google BigQuery,

Getting Started

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Upload the CData JDBC Driver for Salesforce to Google Data Fusion

Upload the CData JDBC Driver for Salesforce to your Google Data Fusion instance to work with live Salesforce 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: cdatasalesforce-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.salesforce) and make note of the name
   • Class name: Set the JDBC class name: (cdata.jdbc.salesforce.SalesforceDriver)
   👁 Configuring the driver (Salesforce is shown.)
   
5. Click "Finish"

Connect to Salesforce Data in Google Data Fusion

With the JDBC Driver uploaded, you are ready to work with live Salesforce 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-salesforce)
   • Set Plugin Type to "jdbc"
   • Set Connection String to the JDBC URL for Salesforce. For example:
     
     jdbc:salesforce:RTK=5246...;InitiateOAuth=GETANDREFRESH;MFACode=YourMFACode

     There are several authentication methods available for connecting to Salesforce: OAuth, Login (or basic), and SSO. The Login method requires you to have the username, password, and security token of the user.

     OAuth Authentication (default)

     The default authentication mechanism (and the one preferred by Salesforce) is OAuth. To use OAuth with CData's embedded OAuth application, leave the connection properties blank. If you have configured your own custom OAuth application with Salesforce (see the Help documentation for more information), set OAuthClientId, OAuthClientSecret, and CallbackURL to the properties for you application. Set InitiateOAuth to the desired OAuth flow ("GETANDREFRESH" will have the connector manage the entire OAuth flow).

     Login (or Basic) Authentication

     If you do not wish do not wish to use OAuth authentication, you can use Login (or basic) authentication. Set AuthScheme to Basic, and set the User, Password, and SecurityToken properties. You can configure your security token in Salesforce.

     SSO (single sign-on) Authentication

     SSO (single sign-on) can be used by setting the SSOProperties, SSOLoginUrl, and SSOExchangeURL connection properties, which allow you to authenticate to an identity provider. See the "Getting Started" chapter in the Help documentation for more information.

     Multi-Factor Authentication (MFA)

     If your Salesforce org has MFA enforcement enabled, set MFACode to the time-based one-time passcode (TOTP) generated by your authenticator app (such as Salesforce Authenticator or Google Authenticator). MFACode applies to both OAuth and Login authentication flows.

     Built-in Connection String Designer

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

      java -jar cdata.jdbc.salesforce.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, 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 salesforce-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 into
   👁 Configuring the BigQuery sink
   

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

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