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:

1. Product catalog

   • Products
   • Plans
   • Add-ons
   • Features

2. Customers

3. Subscriptions

Stigg entity schema

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.
• If BigQuery User is granted at the dataset level, BigQuery Job User must also be granted at the project level to allow users to run queries.

Setup Google Cloud Storage bucket

1. Create a 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.

2. Create an HMAC key

   Create an HMAC key and access ID.

3. Grant the Storage Object Admin role

   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

1. Open the BigQuery integration

   In the Stigg app, navigate to Integrations → Apps → BigQuery.

2. Enter configuration values

   Provide the following details 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 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 path in the GCS bucket where data will be written
   Project ID	The GCP project ID containing the target BigQuery dataset
   Dataset location	The location of your BigQuery dataset
   Dataset ID	The default BigQuery Dataset ID used when the source does not specify a namespace
   Service Account Key JSON	The Google Cloud Service Account Key in JSON format

3. Connect

   Click “Connect to BigQuery” to complete the setup.

Sync process and frequency

1. Initial sync

   Upon completion of the integration setup, Stigg will perform a full sync of all the available data types.

2. Incremental syncs

   Subsequent syncs will be incremental, significantly reducing the amount of data synchronized on a regular basis.

Stigg syncs data to BigQuery daily at 12:00am UTC.

Removing the integration

1. Remove the integration

   Click the dotted menu icon and select Remove.

2. Confirm removal

   In the opened modal, confirm the action by clicking Remove.