> ## Documentation Index
> Fetch the complete documentation index at: https://docs.myquery.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Google BigQuery

> BigQuery is a serverless data warehouse. Connection is handled via Google's Service Account infrastructure.

## **Security & Architecture Overview**

Before connecting your data, it is critical to understand how MyQuery interacts with your infrastructure:

* **Schema-Only Access:** MyQuery does **not** ingest or store your raw database records. We only read the metadata (table names, column types, and foreign key relationships) to build a semantic map for the AI.
* **Encrypted Storage:** All connection credentials and "maps" are encrypted at rest using industry-standard AES-256 encryption.
* **Whitelisting:** To allow MyQuery to reach your database, you must whitelist our outbound IP addresses in your firewall or cloud security groups (e.g., AWS Security Groups, Azure Firewall).

### **Connection Method: Service Account JSON**

* **Step 1: Create Service Account:** In Google Cloud Console, create a service account named

  ```
  myquery-access
  ```

  .
* **Step 2: Assign Roles:** to read schema Grant:

  ```
  BigQuery
  ```

  to run queries:

  ```
  BigQuery Job User
  ```
* **Step 3: Export Key:** Generate a **JSON Key** and download it.
* **Step 4: Connect:** Open the JSON file, copy the object, and paste it into the **Credentials JSON** box in MyQuery.
* **Dataset:** Provide the name of the dataset containing your tables (e.g.,

  ```
  marketing_insights
  ```

  ).