# Google BigQuery

## Create a connection

Ensure that you have a working [connection](https://cloud.google.com/bigquery/docs/connections-api-intro). Connections are [type-specific](https://cloud.google.com/bigquery/docs/connections-api-intro#connection_types) and depend on the connected external data source. Enable the BigQuery Connection API.

Ensure that you can view a [list of service accounts in your project](https://cloud.google.com/iam/docs/service-accounts-list-edit#listing). BigQuery creates and uses a [service account](https://cloud.google.com/iam/docs/service-agents) to connect to your external data source. When you create a connection, a [Google Cloud–managed Identity and Access Management (IAM) service account](https://cloud.google.com/iam/docs/service-account-types#google-managed) is created on your behalf. To view the service account attached to a particular connection, [view the connection details](https://cloud.google.com/bigquery/docs/working-with-connections#view-connections).

You'll need to provide us with your:

* `Project Name`
* `Service Account Credentials` in JSON

## Credential Requirements

Questera AI requires these [permissions](https://cloud.google.com/bigquery/docs/access-control#bq-permissions) to execute BigQuery extracts:

* BigQuery Data Viewer
* BigQuery User
* BigQuery Job User

## Configure in Questera AI

You can test the connection to ensure the credentials were entered properly and are working. An error message will appear if the credentials are not working properly, with some hints as to why we may not be able to connect.


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# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.questera.ai/questera-ai-platform/data/connect-data-and-models/data-sources/google-bigquery.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.
