As a service administrator, you can use the NetSuite Analytics Warehouse extract service to acquire data from the Google Analytics SaaS instance and use it to create data augmentations for various Enterprise Resource Planning and Supply Chain Management use cases.

1. In Google Cloud (Analytics) Project, create a service account and download the credentials.json file.
   See https://cloud.google.com/docs/authentication/production.
2. Add the service account to the Google Analytics 4 property.
   See https://developers.google.com/analytics/devguides/reporting/data/v1/quickstart-client-libraries.
3. Enable Google Analytics APIs using these instructions:
   1. Using a text editor, open the credentials.json file that you had downloaded and search for the client_email field to obtain the service account email address.
   2. Use this email address to add a user to the Google Analytics 4 property you want to access through the Google Analytics Data API v1.
   
4. Ensure that the Google Analytics Admin API, Google Analytics Data API are available for your Google Analytics instance.
   
5. In NetSuite Analytics Warehouse, create the Google Analytics data connection using these instructions:
   1. In NetSuite Analytics Warehouse Console, click Data Configuration under Application Administration.
   2. On the Data Configuration page, click Manage Connections.
   3. On the Manage Connections page, click Create and then click Connection.
   4. In Create Connection, select Data Extraction in Usage Type and then select Google Analytics as the connection type.
      
      

      

      
      
   5. In the dialog for the Google Analytics connection, select Standard as the connectivity type and enter these details:
      • Notification Email: An email address to receive notifications regarding this connection.
      • Service Account Credentials Json File: The Google Cloud Service Account credentials.json file that you had downloaded.
      • Account ID: Google Analytics account ID.
      • GA4 List of Property ID: The GA4 List of Property ID with commas to separate each ID.
      • Lookback Mode: Select either Full or Committed.
      • List of Lookback N days Ago: Comma separated list of days (integer) values such as 7,21.

      

      Note these:

      • For the Lookback mode, if you don't provide a value, then the Lookback mode isn't supported. The Full option requires one day value, if you provide multiple values, then the process uses the first value. You can provide multiple values for the Committed option.
      • For List Data Stores, the REST API returns a list of GA4 Property IDs either using the Account ID (if provided) or just the source configured or provided list of property.
      • For List columns, the REST API returns a list of column metadata for the given GA4 Property ID.
   6. Verify that the Refresh Metadata toggle is enabled to ensure that the metadata is refreshed when you save the connection.
      You can later refresh the metadata from the Actions menu on the Manage Connections page, if required.

      Note:

      You can’t create augmentations for Google Analytics unless you perform a metadata extract.

      Metadata extract:

      • Retrieves metadata columns for each GA4 Property ID provided in the source configuration.
      • Prefixes the GA property columns with Dimension_ orMetric_ that NetSuite Analytics Warehouse later uses while extracting data to differentiate Dimension and Metric column type.
      • Leaves the payload dataStores array empty.
   7. Click Save.
6. On the Manage Connections page, select Actions for the Google Analytics connection and then select Test Connection.

   Note:

   REST API signature is same across sources. Test connection invokes GA Common Metadata API. This returns the default version values and no calls are made to the source.
7. To delete a connection, on the Manage Connections page, click Actions for the applicable connection and select Delete.

   Note:

   Ensure that you delete the functional areas, data augmentations, and custom data configurations related to the data connection before deleting it. You can't update or load data from deleted data connections to the warehouse.
8. After the connections are successfully established, navigate to the Data Configuration page, select the connection in Data Source, then click the Data Augmentation tile, and create a data augmentation using the Google Analytics data. Select the applicable Google Analytics source tables. Ensure that you specify “Dimension_transactionId” in the source tables as the primary key and use it to join each of the data augmentation tables. You can select a maximum number of nine dimensions for each data augmentation. See Augment Your Data.
   When you enable data extraction, you can schedule to run when you choose to do so. For data extraction, note these:

   1. Provide date ranges to run the report and fetch data.
   2. Regular data extract uses the initial or last ExtractDate as StartDate and job RunDate as EndDate.
   3. Lookback mode includes additional date ranges along with the regular extract date range which fetches additional data set but in a single runReport call.
      • The Full option has a single date range; StartDate=ExtractDate - NdaysAgo, EndDate=RunDate.
      • The Commited option can have multiple date ranges. For each configured GA_LIST_OF_N_DAYS_AGO, StartDate=ExtractDate - NdaysAgo, EndDate=RunDate - NdaysAgo.