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

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

Upload the CData JDBC Driver for Adobe Analytics to your Google Data Fusion instance to work with live Adobe 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: cdataadobeanalytics-2020.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.adobeanalytics) and make note of the name
   • Class name: Set the JDBC class name: (cdata.jdbc.adobeanalytics.AdobeAnalyticsDriver)
5. Click "Finish"

Connect to Adobe Analytics Data in Google Data Fusion

With the JDBC Driver uploaded, you are ready to work with live Adobe 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
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-adobeanalytics)
   • Set Plugin Type to "jdbc"
   • Set Connection String to the JDBC URL for Adobe Analytics. For example:
     
     jdbc:adobeanalytics:RTK=5246...;GlobalCompanyId=myGlobalCompanyId; RSID=myRSID; OAuthClientId=myOauthClientId; OauthClientSecret=myOAuthClientSecret; CallbackURL=myCallbackURL;

     Adobe Analytics uses the OAuth authentication standard. To authenticate using OAuth, you will need to create an app to obtain the OAuthClientId, OAuthClientSecret, and CallbackURL connection properties. See the "Getting Started" section of the help documentation for a guide.

     Retrieving GlobalCompanyId

     GlobalCompanyId is a required connection property. If you do not know your Global Company ID, you can find it in the request URL for the users/me endpoint on the Swagger UI. After logging into the Swagger UI Url, expand the users endpoint and then click the GET users/me button. Click the Try it out and Execute buttons. Note your Global Company ID shown in the Request URL immediately preceding the users/me endpoint.

     Retrieving Report Suite Id

     Report Suite ID (RSID) is also a required connection property. In the Adobe Analytics UI, navigate to Admin -> Report Suites and you will get a list of your report suites along with their identifiers next to the name.

     After setting the GlobalCompanyId, RSID and OAuth connection properties, you are ready to connect to Adobe Analytics.

     Built-in Connection String Designer

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

     java -jar cdata.jdbc.adobeanalytics.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 Adobe Analytics, i.e.:
     SELECT * FROM AdsReport
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 adobeanalytics-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 Adobe Analytics data into

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

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