BigQuery
Learn about Stigg's native integration with BigQuery
Overview
Stigg's integration with BigQuery serves a core principal of granting access to raw data, enabling the creation of customized reporting solutions and fostering informed business decision-making.
Stigg's native integration with BigQuery is included in the Scale plan, and is also available as an optional add-on to the Growth plan. See Stigg's pricing for more details.
Available data types
Stigg's integration with BigQuery allows you to sync the following Stigg entities to BigQuery:
- Product catalog
- Products
- Plans
- Add-ons
- Features
- Customers
- Subscriptions
Setting up the integration
Prerequisites
- A Google Cloud project with BigQuery enabled.
- A BigQuery dataset to sync data to.
- A Google Cloud Service Account with the BigQuery User, BigQuery Data Editor and Storage Object Admin roles and the Service Account Key in JSON format.
Setup Google Cloud Storage bucket
- Create a Cloud Storage bucket with the Protection Tools set to none or Object versioning. Make sure the bucket does not have a retention policy.
- Create an HMAC key and access ID
- Make sure the Storage Object Admin role is granted to the Google Cloud Service Account. This must be the same service account as the one you configure for BigQuery access.
Your bucket must be encrypted using a Google-managed encryption key (this is the default setting when creating a new bucket).
Bucket encryption using customer-managed encryption keys (CMEK) is not currently supported.
You can view this setting under the "Configuration" tab of your GCS bucket, in the Encryption type row.
Connect Stigg with BigQuery
In the Stigg aa, navigate to the Integrations > Apps > BigQuery section.
Enter the below information in the opened form:
Field | Description |
|---|---|
| HMAC Key Access ID | The HMAC key access ID used to access the GCS bucket. |
| HMAC Key Secret | The the HMAC key secret used to access the GCS bucket. |
| GCS Bucket Name | The name of the GCS bucket that will be used in the integration. |
| GCS Bucket Path | The directory under the GCS bucket where data will be written. |
| Project ID | The GCP project ID for the project containing the target BigQuery dataset. |
| Dataset location | The location of your BigQuery dataset. |
| Dataset ID | The default BigQuery Dataset ID that tables are replicated to if the source does not specify a namespace. |
| Service Account Key JSON | The Google Cloud Service Account Key in JSON format. |
Click "Connect to BigQuery".
Sync process and frequency
Upon completion of the integration setup, Stigg will perform a full sync of all of the available data types.
Subsequent syncs will be incremental; thereby, significantly reducing the amount of data synchronized on a regular basis.
Stigg syncs data to BigQuery on a daily basis at 12:00am UTC.
Removing the integration
To remove the integration, click on the dotted menu icon and select the "Remove" action.
Confirm the action by clicking on the "Remove" button in the opened modal.
Updated 6 months ago