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

Upload the CData JDBC Driver for Google Analytics to Google Data Fusion

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

Connect to Google Analytics Data in Google Data Fusion

With the JDBC Driver uploaded, you are ready to work with live Google Analytics 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-googleanalytics)
   • Set Plugin Type to "jdbc"
   • Set Connection String to the JDBC URL for Google Analytics. For example:
     
     jdbc:googleanalytics:RTK=5246...;Profile=MyProfile;InitiateOAuth=GETANDREFRESH;

     Google uses the OAuth authentication standard. To access Google APIs on behalf on individual users, you can use the embedded credentials or you can register your own OAuth app.

     OAuth also enables you to use a service account to connect on behalf of users in a Google Apps domain. To authenticate with a service account, register an application to obtain the OAuth JWT values.

     In addition to the OAuth values, set Profile to the profile you want to connect to. This can be set to either the Id or website URL for the Profile. If not specified, the first Profile returned will be used.

     Built-in Connection String Designer

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

      java -jar cdata.jdbc.googleanalytics.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 Google Analytics, i.e.:
     SELECT * FROM Traffic
   👁 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 googleanalytics-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 Google Analytics data into
   👁 Configuring the BigQuery sink
   

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

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