Google Analytics 360

Google Analytics 360 (GA 360) is a marketing analytics platform that helps you obtain actionable insights from your data. You can retrieve the GA 360 data in two forms:

  • Unsampled reports in dashboard.

  • Unsampled event level data that you can export to a Google BigQuery project using the BigQuery Export feature. For this, you must link your GA 360 account to a Google BigQuery (BigQuery) project. The data is stored in tables within datasets that reside in the BigQuery project.

Hevo uses the BigQuery API to read the data exported to BigQuery tables and replicate it to a Destination system of your choice.


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 Asset Palette.

  2. Click + CREATE in the Pipelines List View.

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

  4. In the Configure your Bigquery Account linked to Google Analytics 360 page, click + ADD BIGQUERY ACCOUNT.

  5. Select your linked Google account with BigQuery DataViewer privilege, and click Allow to provide Hevo read access to your analytics data.

    Click Allow

  6. In the Configure your Google Analytics 360 Source page, specify the following:

    Test & Continue

    • 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.


      • 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 the past data must be ingested. Default value: All Available Data.

  7. Click TEST & CONTINUE.

  8. Proceed to set up the Destination.

Creating your BigQuery Project

You need to link your GA 360 account to the BigQuery project where you want to export the data. To create your BigQuery project, you need to have a Google Cloud project with BigQuery API enabled. To do this:

1. Create a Google Cloud project

Note: Skip this step if you want to use an existing Google Cloud project.

  1. Log in to the Google Cloud Console.


  3. In the New Project page, specify the following:

    New project

    • Project name: A unique name for your project.

    • Organization: The organization to attach to your project.

    • Location: The parent organization or folder for your project.

  4. Click CREATE.

This creates a Google Cloud project.

2. Enable the BigQuery API

Note: Skip this step if you already have the BigQuery API enabled for your organization.

  1. Log in to the Google Cloud Console.

  2. In the left navigation menu, click APIs & Services, and then, click Library.

    Click Library

  3. In the API Library page, search for BigQuery API, and then, click ENABLE.

    Click enable

This enables your BigQuery project.

BigQuery charges you for the data you are storing in it. For this, it requires you to have an active billing account in your BigQuery project. A single billing account may be shared across multiple projects.

To link a billing account:

  1. Log in to the Google Cloud Console.

  2. In the left navigation pane, click Billing.

    Note: If you already have a billing account linked to your BigQuery project, the following screen is prompted by the application. In such case, skip to Linking the Google Analytics 360 account to the BigQuery Project.

    Multiple account

  3. In the Billing page, click LINK A BILLING ACCOUNT.

    Link account


    Create account

  5. Follow the steps in the screens, as prompted by the application, to create your billing account.

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:

The service account must have Editor permission at the project level. Read more. 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.

    Click IAM

  3. Click ADD.

    Click Add

  4. In the Add members to <your project name> page, specify the following:

    • New members:

    • Select a role: Editor

  5. Click Save.

  1. Login to your GA 360 account as an Owner with Edit privilege to edit the permissions for the analytics property.

    Click here and check your Role. If you are not an Owner, contact your project Owner to perform the following steps.

  2. In the left navigation pane, click Admin.

  3. In the ADMIN page, under Property, select <your property name> from the drop-down, and then, click All Products.

    Click all products

  4. Click Link BigQuery.

  5. Enter your BigQuery project number or ID. To locate your BigQuery project ID, read this.

  6. Select the View you want to link.

  7. Click Save.

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.

Data Replication

Default Pipeline Frequency Minimum Pipeline Frequency Maximum Pipeline Frequency Custom Frequency Range (Hrs)
1 Hr 15 Mins 24 Hrs 1-24

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

  • Historical Data: Hevo ingests historical data for all the objects on the basis of the historical sync duration selected at the time of creating the Pipeline.

  • Incremental Data: Once the historical data is ingested, each subsequent run of the Pipeline fetches new and updated data.

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:

Objects Description
ga_sessions Contains the session-level data.
hits/ ga_session_hits Contains the hit-level data depending on the parsing strategy.

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


Revision History

Refer to the following table for the list of key updates made to this page:

Date Release Description of Change
Oct-25-2021 NA Added the Pipeline frequency information in the Data Replication section.
Mar-23-2021 1.59 New document.
Last updated on 19 Aug 2022

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