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Setting up your Enterprise account

This article shows you how to enable the Enterprise account for your Analytics Canvas subscription. The Enterprise subscription allows you to use your organization's BigQuery Project for data processing and storage.

With this access, you can query your GA4 Property and any other Projects that you authorize.  The billing is directed to your Google Cloud account, where it is governed by your Google Cloud budget.

Using a Service Account with your Enterprise Subscription

The recommended method for accessing Google BigQuery and Google Cloud Storage within applications is to use a Google Cloud Service Account, which belongs to an application rather to an individual user.

Find your Analytics Canvas Service Account under Admin > Access your own BigQuery 


Creating a Google Cloud Project for Analytics Canvas 

In the Google Cloud console, create a Project to hold application data.  This includes all data ingested into Analytics Canvas Online, all temporary tables created for working within the application, all cache tables, and all Looker Studio output tables. 

  1. Login to https://console.cloud.google.com/bigquery
  2. Create a Google Cloud Project for use with Analytics Canvas.  It would be helpful to include "AnalyticsCanvas" and "AppData" in the project name.
  3. Restrict access to this project.  Do not give anyone else access to this project to read from or write data into.  
  1. Go to IAM and provide your Analytics Canvas Service account with access to the project. This project requires: 
    • BigQuery Data Owner
    • BigQuery Job User

When you have completed all of the steps below, Analytics Canvas will create datasets in the project that it will use. You will find them in the BigQuery console.


Creating a Google Cloud Storage bucket to use within the project

  1. Next, go to Cloud Storage and create a new bucket.
  1. Provide a name for your bucket, then choose a data location.  The location should be the same as your app data project. 
  1. Use the default / standard storage class.
  1. Select Uniform level of Access Control.
  1. No additional Protection tools are required.  Click "Create" to complete the setup of your bucket.

Permissions to use the GCS bucket

With the bucket created, the Service Account now needs access to it.

  1. Go to Cloud Storage
  2. Select the correct Project
  3. Select the bucket that was created for use with Analytics Canvas
  4. Navigate to +Grant Access
  5. Add permission "Storage Admin" for the Service Account used in your Analytics Canvas subscription

Your Google Cloud Storage bucket is now ready for use in Analytics Canvas. 


Ensuring your Google Cloud Project is ready to be used by an Application

Certain APIs must be authorized with your Google Cloud Platform Project to enable access to BigQuery and Google Cloud Storage. 

  • To see and display your projects and the permissions associated with your Service Account, enable the Cloud Resource Manager API (click the link to open this API in your browser after logging in to the Google Cloud Console).
  1. If you will be connecting to BigQuery, the BigQuery API must be enabled
  1. Finally, you must enable the Cloud Storage API

With the above APIs enabled, you are now able to connect to the dataset with an application.  

Connecting Analytics Canvas to your Google Cloud Project

Now that the projects are created and enabled in the Google Cloud Console, it is time to configure your Analytics Canvas account to use them.

  1. In Analytics Canvas, go to Admin > BigQuery Quota and Location
  2. Under "Your Own BigQuery Account", select "Add Location"
  3. Canvas should now detect that you have a project and billing project authorized.  Select them from the drop down lists.
  4. For the Data Cache Project, select the BigQuery project you setup for use with Analytics Canvas.
  5. Enter the exact name of the Google Cloud Storage Temp bucket, then click Validate.
  6. Once all of your configurations are set, click "Create Environment"

You are now setup to use your own BigQuery account for storage and processing.  However, note that so far you have only provided access to the project that the application will run in.  You can connect to APIs, databases, and Google Sheets and the tables will be cached, stored, and processed in this project.  Looker Studio datasets will also be hosted in this project.

Creating a Canvas in your Own BigQuery Project

Be sure to create your Canvases within the User Billed BigQuery Location. To connect to your own BigQuery data, follow these instructions

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