Google BigQuery
This page describes how to configure Google BigQuery credentials for use by Census and why those permissions are needed.

These instructions are well tested to connect Census to BigQuery. If you're running into connection issues or missing tables or views, please confirm you've run all of these instructions.
Census reads data from one or more tables (possibly across different schemata) in your data warehouse and publishes it to the corresponding objects in external systems, such as Salesforce. To limit the load on your database as well as external APIs, Census computes a โ€œdiffโ€ to determine changes between each update. In order to compute these diffs, Census creates and writes to a number of tables in the CENSUS dataset ('dataset' is what Google calls their equivalent of a 'schema' in standard database terminology).In order for the Census connection to work correctly, the account you provide to Census must have these permissions:
  • Full admin access to all schema/tables within the CENSUS dataset (including creating and deleting tables, and reading and writing to all tables).
  • Read-only access to any tables and views in any schemata that you would like Census to publish to Salesforce.
  • Permissions to create jobs in order to unload data.
BigQuery manages these permissions through their IAM Policy mechanism. Specifically, Census uses three BigQuery policies by default:
  • bigquery.dataViewer - Allows Census read-only access to list the datasets and tables in the BigQuery instance, and to get data from the tables.
  • bigquery.dataEditor - Allows Census full-admin access to the tables in the CENSUS dataset.
  • bigquery.jobUser - Allows Census to create jobs to unload data.

We definitely recommend you use the three permissions we specify when creating a new BigQuery connection. If you cannot grant these permissions at the project level, you can grant them finer grain. These are the specific permissions the Census service account needs:
  • bigquery.dataViewer access on the dataset or specific table you'd like Census to read from.
  • bigquery.dataEditor access on the CENSUS dataset OR bigquery.dataOwner access on the CENSUS dataset if you would like to additionally grant Census permissions to delete the CENSUS dataset
  • Finally, Census service account needs project-level access with the bigquery.JobUser role or specifically the bigquery.jobs.create permission (via a custom role).

Because permissions are a bit unique on BigQuery so the process of creating a new connection to Census requires a few extra steps.
  1. 1.
    Visit the Connections section on Census, and press Add Data Warehouse Connection, selecting BigQuery from the list.
  2. 2.
    Census will ask you to provide the Google Cloud Project ID that contains your BigQuery instance. You can find that on the Google Cloud Console in the Project Info section. If you have multiple Google Cloud projects, you'll need to first select the correct one with the project picker in the top right.
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  3. 3.
    You will also need to specify in what location you want your Census Dataset to be stored in. This locality will be used in the 1st and 2nd command below, and this dataset is where Census will store its bookkeeping to make sure that only incremental changes are synced to your destinations.
  4. 4.
    Once you've provided Census with your Project ID, Census will automatically generate a new Role Account we'll use to communicate with your BigQuery and provide you with one command to create the CENSUS dataset and three copy and paste-able commands you can use to grant permissions for this account on this project. The second command grants dataEditor on the newly created CENSUS dataset.
1st and 2nd commands
The third command grants dataViewer to the Census serviceAccount, and the fourth command grants jobUser to the Census serviceAccount. Both of these are executed at the level of the project to which you are giving access to Census to give visibility to.
3rd and 4th commands
The easiest way to execute these commands is within the Google Cloud Shell in the Google Cloud Console, however the third block can also be managed within the BigQuery IAM permissions to grant to the exact datasets that you want to give Census access to sync data from.
5. Once you've run all the commands, press the Test button in Census. This will validate that you've granted the appropriate credentials. Once you've got a checkmark for all four steps, you're good to go!
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BigQuery supports External Tables which allows Google Sheets and tabular data in Google Drive to appear as tables in BigQuery. In order for Census to access these resources, it must be given explicit access to the Google Sheet or Google Drive document.
  1. 1.
    First, you'll need the Census service account's email address for your specific connection. You can see that in the Connections Tab. It's of the form census-[LONG ID]@sutrolabs-giza-production.iam.gserviceaccount.com
  2. 2.
    Next, in Google Drive, click Share and give that email address permission to View the contents of the document.
If Census does not have view access to the document, you will see an error indicating that Census does not have permission to access the underlying data for that table.

It's possible to create views in a BigQuery project that reference the tables and views present in other BigQuery projects. In order for Census to access these types of views within your project, it must also be granted permissions in the other projects that contain the referenced tables and views. If you are using the default IAM policies that Census recommends, you may run the following commands in your Google Cloud Shell in the Google Cloud Console, where:
  • [new-project] is the name of the project where the referenced tables and views exist.
  • [service-account-user] is the Census service account's email address for the specific connection that contains the view you're trying to access. You can see that in the Connections Tab. It's of the form census-[LONG ID]@sutrolabs-giza-production.iam.gserviceaccount.com
gcloud projects add-iam-policy-binding [new-project] \
--member serviceAccount:[service-account-user] \
--role roles/bigquery.dataViewer
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gcloud projects add-iam-policy-binding [new-project] \
--member serviceAccount:[service-account-user] \
--role roles/bigquery.user
Google BigQuery permissions are recursive. If the referenced view in the new project also references tables and views in other projects, you may need to repeat the above steps for those other projects until Census has the ability to access the ultimate source of a given view.

While BigQuery itself doesn't support IP allow lists, you can use VPC Service Controls to wrap your BigQuery instance and limit access. Census will always connect to your data warehouse from these static IP addresses:
  • 34.216.163.241
  • 54.212.243.205
When using VPC Service Controls, you will also need to allow BigQuery unloads to the Census GCP bucket. To do that, you'll need to add gs://sutrolabs-giza-unloads-production in the allow list for BigQuery unloads.

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On this page
๐Ÿ“บ How-To Configure BigQuery Video
๐Ÿ” Required permissions
๐Ÿ”ฉ Configuring a new BigQuery connection
๐Ÿ—ƒAccessing Google Sheets and Google Drive tables in BigQuery
๐Ÿ—ƒAccessing views that depend on other projects in BigQuery
๐ŸšฆVPC Service Controls and IP Restrictions
๐Ÿš‘ Need help connecting to BigQuery?