Prerequisites

• An active Google Analytics 360 (GA 360) account from which data is to be ingested exists.

• A BigQuery project is created to load your GA 360 data.

• The GA 360 account is linked to your BigQuery project.

• BigQuery Data Viewer privilege is granted to the Google account used to authenticate the GA 360 account.

• You are assigned the Team Administrator, Team Collaborator, or Pipeline Administrator role in Hevo to create the Pipeline.

Creating your BigQuery Project

Linking the Google Analytics 360 account to the BigQuery Project

1. Add the service account to your BigQuery project

You must add the following service account as a member of the BigQuery project:

analytics-processing-dev@system.gserviceaccount.com

The service account must have Editor permission at the project level. Learn more about setting up permissions. GA 360 uses this service account to export your data to your BigQuery project.

1. Log in to the Google Cloud Console.

2. In the left navigation pane, click IAM & Admin, and then click IAM.

   

3. On the IAM page, under the VIEW BY PRINCIPALS tab, click GRANT ACCESS.

   

4. On the Grant access to <your project name> slide-in page, specify the following:

   • Add principals: analytics-processing-dev@system.gserviceaccount.com

   • Assign roles: Editor

   

5. Click Save.

2. Link your Google Analytics 360 account to your BigQuery project

1. Login to your GA 360 account with Editor access to modify permissions for the Analytics property and Owner access to manage the BigQuery project.

   Click here to check your role in the BigQuery project you want to link. If you are not an Owner, contact your project owner to perform the following steps.

2. In the left navigation pane, click Admin.

3. On the Admin page, in the PROPERTY SETTINGS section, under Product links, click BigQuery links.

   

4. Click Link.

   

5. On the Create a link with BigQuery slide-in page, click Choose a BigQuery project.

   

6. Select the checkbox next to the project you want to link and then click Confirm.

   

7. Click Next to configure the Event data and User data in the Configure settings section.

8. Click Next to review your specified configuration settings and click Submit.

Once you link your GA 360 account to your BigQuery project, you must refresh the Configure your Google Analytics 360 Source page in Hevo to reflect the updated project and dataset IDs.

Note: BigQuery tables take 24 hours to display the data when you set up your BigQuery Export for the first time.

Configuring Google Analytics 360 as a Source

Perform the following steps to configure GA 360 as a Source in Hevo:

1. Click PIPELINES in the Navigation Bar.

2. Click + CREATE PIPELINE in the Pipelines List View.

3. On the Select Source Type page, select Google Analytics 360.

4. On the Configure your Bigquery Account linked to Google Analytics 360 page, do one of the following:

   • Select a previously configured account and click CONTINUE.

   • Click + ADD BIGQUERY ACCOUNT and perform the following steps to configure an account:

     1. Select your linked Google account with BigQuery DataViewer privilege.

     2. Click Allow to provide Hevo read access to your analytics data.

        

5. On the Configure your Google Analytics 360 Source page, specify the following:

   

   • Pipeline Name: A unique name for your Pipeline, not exceeding 255 characters.

   • Project ID: The ID of your BigQuery project linked to the GA 360 account.

     Note: If you are linking your GA 360 account to your BigQuery project for the first time, you must refresh this page in Hevo to reflect the updated project IDs.

   • Dataset ID: Name of the dataset which contains your Google Analytics 360 data. Once your GA 360 account is linked to your BigQuery project, the dataset ID becomes available for selection in the drop-down. If you do not find your dataset ID listed in the drop-down, contact Hevo Support.

     Notes:

     • You can select multiple dataset IDs from the drop-down.

     • By default, Hevo loads a maximum of 500 dataset ID in the Dataset ID drop-down.

     • GA 360 refers to the dataset as View.

   • Historical Sync Duration: The duration for which you want to ingest the existing data from the Source. Default duration: All Available Data.

     Note: If you select All Available Data, Hevo ingests all the data available in your Google Analytics 360 account since January 01, 2016.

6. Click TEST & CONTINUE.

7. Proceed to set up the Destination.

Data Replication

Note: The custom frequency must be set in hours as an integer value. For example, 1, 2, or 3 but not 1.5 or 1.75.

• Historical Data: The first run of the Pipeline ingests historical data for the selected objects on the basis of the historical sync duration specified at the time of creating the Pipeline and loads it to the Destination.

• Incremental Data: Once the historical load is complete, data is ingested as per the ingestion frequency in Full Load or Incremental mode, as applicable.

Your GA 360 data is stored in the following tables in BigQuery:

• ga_sessions_YYYYMMDD: This table is generated at the end of the day. Once the table is generated, the data in this table is not modified. Hevo reads this table only once.

• ga_sessions_intraday_YYYYMMDD: This table is generated multiple times a day and is deleted the next day after the ga_sessions_YYYYMMDD table is generated for the previous day. The data in this table changes throughout the day. Hevo ingests data once an hour by default. You can configure this frequency using the Change Schedule option in the Pipeline Summary Bar.

Schema and Primary Keys

Hevo uses the following schema to upload the records in the Destination system:

Note: _hevo_id is a primary key generated by hashing date, visitor_id, visit_id, visit_start_time.

Data Model

Depending on the selected parsing strategy, there can be one or more objects in the Destination system.

The following table lists the two important objects that are critical to GA 360’s functioning:

The schema of the table is generated based on the Destination and the selected parsing strategy.