BigQuery
BigQuery
NinjaCat supports connecting to Google BigQuery as a custom dataset source. This allows you to query data stored in your BigQuery project and surface it in NinjaCat reports and Data Cloud.
Prerequisites
Before setting up a BigQuery connection, ensure you have:
- A Google Cloud project with BigQuery enabled
- A service account with at minimum BigQuery Data Viewer and BigQuery Job User roles
- The service account's JSON key file
- The name of the BigQuery dataset and the table or view you want to query
Setting Up a BigQuery Connection
BigQuery connections can be configured in two places:
- Classic dataset editor — the traditional connection form
- Custom Mapped Dataset wizard — the modern step-by-step setup experience
Both surfaces expose the same connection fields, including the new Dataset Location field described below.
Connection Fields
| Field | Required | Description |
|---|---|---|
| Project ID | Yes | Your Google Cloud project ID |
| Dataset | Yes | The BigQuery dataset name |
| Table / View | Yes | The table or view to query |
| Service Account JSON | Yes | Contents of your service account key file |
| Dataset Location | No | The region where your BigQuery dataset resides (e.g., US, EU, us-central1, us-east4). Leave blank to use the default behavior (US multi-region). |
Dataset Location Field
What It Does
The Dataset Location field is a free-text input field. Enter the region identifier that matches the location of your BigQuery dataset — for example:
US(US multi-region, the default if left blank)EU(Europe multi-region)us-central1us-east4
When to Use It
Set the Dataset Location field if your BigQuery dataset is stored outside the US multi-region (i.e., any region other than US). If you have previously seen errors like:
Not found: Job <project>:<job_id> was not found in location USthis field resolves those errors by telling NinjaCat which region to route queries to.
Existing connections are unaffected when the field is left blank. Leaving it blank preserves the previous default behavior (US multi-region).
How to Find Your Dataset's Location
- Open the Google BigQuery console
- Expand your project and select the dataset
- Click Dataset info — the Data location field shows the region
Enter that value exactly (case-sensitive) in the Dataset Location field in NinjaCat.
On-Screen Connection Errors
Connection and region errors are now surfaced directly on screen as you set up or edit a dataset. If NinjaCat cannot connect to your BigQuery dataset, you will see an error message displayed as a notification.
Note on error messages: The error text shown is passed through from Google's API response. Messages may include Google's raw error text, such as:Not found: Job <project>:<job_id> was not found in location USIf you see a message referencing an unexpected location (e.g.,
location USwhen your data is ineu-west1), set the Dataset Location field to match your dataset's actual region in BigQuery.
Troubleshooting
| Symptom | Likely Cause | Resolution |
|---|---|---|
| Columns fail to load; no error shown | Region mismatch | Set the Dataset Location field to match your dataset's region in BigQuery |
Error: Not found: Job … was not found in location US | Dataset is outside US multi-region | Set Dataset Location to the correct region (e.g., EU, us-central1) |
Error: Access Denied | Service account permissions | Ensure the service account has BigQuery Data Viewer + BigQuery Job User roles |
| Connection succeeds but data is empty | Table/dataset name mismatch | Verify the dataset and table names are correct and accessible to the service account |
Related Pages
- BigQuery Fields — Available dimensions and metrics for BigQuery datasets