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

Upload the CData JDBC Driver for ADP to Google Data Fusion

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

Connect to ADP Data in Google Data Fusion

With the JDBC Driver uploaded, you are ready to work with live ADP 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-adp)
   • Set Plugin Type to "jdbc"
   • Set Connection String to the JDBC URL for ADP. For example:
     
     jdbc:adp:RTK=5246...;OAuthClientId=YourClientId;OAuthClientSecret=YourClientSecret;SSLClientCert='c:\cert.pfx';SSLClientCertPassword='admin@123';InitiateOAuth=GETANDREFRESH;

     Connect to ADP by specifying the following properties:

     • OAuthClientId: The client Id of the custom OAuth application you obtained from ADP.
     • OAuthClientSecret: The custom OAuth application's client secret.
     • SSLClientCert: Set this to the certificate provided during registration.
     • SSLClientCertPassword: Set this to the password of the certificate.
     • UseUAT: The connector makes requests to the production environment by default. If using a developer account, set UseUAT = true.
     • RowScanDepth: The maximum number of rows to scan for the custom fields columns available in the table. The default value will be set to 100. Setting a high value may decrease performance.

     The connector uses OAuth to authenticate with ADP. OAuth requires the authenticating user to interact with ADP using the browser. OAuth access can be configured in ADP through ADP API Central. For more information, refer ADP's API Central Quick Start Guide and the OAuth section in CData's Help documentation.

     Built-in Connection String Designer

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

      java -jar cdata.jdbc.adp.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 ADP, i.e.:
     SELECT * FROM Workers
   👁 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 adp-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 ADP data into
   👁 Configuring the BigQuery sink
   

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

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