Google BigQuery is an enterprise data warehouse for large-scale data analytics. You can connect Quantive to any table in a BigQuery dataset and create a Quantive entity based on it.
Prerequisites
Quantive supports two ways of integrating with Google BigQuery – using a Quantive-provided service account or using a service account owned by the user.
Using the Quantive-provided service account.
Quantive uses a service account with OAuth 2.0 authentication/authorization flow. Before you establish a connection to your BigQuery data set you need to make sure that the Quantive Service Account for Google API has been added to your project and assigned the necessary permissions. We recommend that you use a custom role and assign this role to the service account.
Creating a custom role in the Google Cloud Platform
To create a custom role log in to your Google Cloud Platform account and navigate to the Console. Select the project where you want to create the custom role, then from the menu choose IAM & Admin > Roles.
1. Click the Create Role button
2. Fill in details for the role you will be creating.
3. Add the following permissions:
big query.datasets.get
bigquery.jobs.create
bigquery.tables.get
bigquery.tables.getData
bigquery.tables.list
bigquery.readsessions.create
4. Click the Create button.
Adding Quantive Service Account to Cloud Platform project
In the IAM & Admin management console go to the IAM section. Click on the Add button to add the Quantive Service account, then use gtmhub-sync@useful-citizen-108308.iam.gserviceaccount.com as the user email. Finally set the custom role created earlier.
Using a user-owned service account
In the case of a user-provided Google service account, you need to download the key in the form of a JSON file from the Google Cloud Developer website. To do it, you have to go to the Google Cloud Platform > Service Accounts > select your service account.
Then go to Keys > Add key > Create new Key.
Select JSON and click Create. This will download the JSON file to your PC.
How to connect
Quantive-provided service account
In Quantive, navigate to Settings > Data Sources screen
Click the Select data source button
From the Choose a connector dialog, select the Databases tab and then Google BigQuery
Enter the necessary information to connect to your BigQuery dataset.
Project ID - this is the ID of the project where your dataset lives.
Dataset ID - this is the ID of the dataset you wish to connect to.
Google JSON – leave it blank.
Click on the Connect button.
If Quantive has been granted the necessary permissions to read data from BigQuery you will be able to choose the table you want to pull data from.
4. Define who will have access and who will be able to administrate this connection using Data Connection permissions.
5. Select the table you want. Give it a name and choose its sync schedule.
6. Finally define permission to allow eligible users to be able to access the information.
User-owned service account
In Quantive, navigate to Settings > Data Sources screen
Click the Select data source button
From the Choose a connector dialog, select the Databases tab and then Google BigQuery
Enter the necessary information to connect to your BigQuery dataset.
Project ID - this is the ID of the project where your dataset lives.
Dataset ID - this is the ID of the dataset you wish to connect to.
Google JSON – copy and paste the contents of the downloaded JSON file.
Click on the Connect button.
If Quantive has been granted the necessary permissions to read data from BigQuery you will be able to choose the table you want to pull data from.
4. Define who will have access and who will be able to administrate this connection using Data Connection permissions.
5. Select the table you want. Give it a name and choose its sync schedule.
6. Finally define permission to allow eligible users to be able to access the information.