Introduction
The BigQuery integration enables you to ask questions in natural language, which are automatically translated into SQL to analyze your data directly from BigQuery. See example result below for the query “give me progression in temperature for Havana and plot it” for a user who connected Sana to their database with weather data.
Integration capabilities
With this integration, you can perform real-time read operations on your BigQuery data within Sana Agents. There’s no need for regular data syncing as queries are executed live. The integration allows you to select and describe which BigQuery views you want to make accessible in Sana.
Operation type | Supported |
Read | ✅ |
Write | ❌ |
Type of integration
Shared: Set up by an admin for a workspace or collection, with access managed within Sana.
Availability
Integration type | Free tier | Team tier | Enterprise tier |
Private | ❌ | ❌ | ❌ |
Shared | ❌ | ❌ | ✅ |
Centralized | ❌ | ❌ | ❌ |
Integration set-up
1. Find and click on “BigQuery” integration inside of the list of available integrations.
2. Click “Connect shared”
3. Paste or upload your BigQuery credentials in JSON format. Click “Format JSON” and “Test connection” before proceeding to “Continue”.
4. Select the views you want to be able to access.
Click “Add view,” then choose “Browse views” to import existing ones or “Create view” to define a new view from scratch.
Browse views: Select dataset locations (if applicable), check the views you want, and click “Import views.”
Create view manually: Enter the required fields and your query, click “Sync,” and once successful, click “Create view.”
Click “Continue” after all your views have been successfully synced.
Tips and best practices when creating views:
To edit or delete a view, click the three dots next to its status badge.
Add descriptive titles, descriptions, and column details to help the agent generate accurate SQL queries and make data discovery easier.
5. Select who to share the integration with and add optional title and description.
Known limitations
BigQuery only supports views from one dataset location per integration. I.e, you can not create an integration to BigQuery which combines views that are stored in different dataset locations. Dataset location can not be changed after an integration has been created. If you want a view in another location, create a new integration.
Sana Agents does not support write operations to BigQuery (i.e., creating and updating data)
FAQ
Q: What is a view?
A: A view can be described as a saved SQL query in BigQuery used for simplify sharing of common data that you want to make easily accessible by others. Inside of Sana you can then choose to import a view to make it part of your integration to BigQuery.
Q: How often is the data synced?
A: The data is synced in real-time.
Q: Can I create, update or delete data in BigQuery from Sana?
A: No, this integration currently only supports read operations.
Data handling & privacy
Sana AI is fully committed to data security and privacy. All data accessed by Sana AI is encrypted both in transit and at rest. Sana does not train any underlying language models on your data, ensuring the privacy of your information. Sana AI is ISO 27001 certified; and SOC 2 and GDPR compliant, and adheres to the highest standards of data security.