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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.

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Exported entities

When connecting BigQuery, you can choose which Stigg entity groups to include in the sync. All groups are selected by default. See Exported entities for the full list of entity groups and the tables within each.
  • Products
  • Plans
  • Add-ons
  • Features
  1. Customers
  2. Subscriptions
  3. Usage data
    • Usage events (USAGE_EVENT_<ENVIRONMENT_ID>)
    • Credits usage (CREDITS_USAGE_<ENVIRONMENT_ID>)
Usage events and credits usage export originates from ClickHouse and must be enabled by Stigg support. Once enabled, the tables will appear in your BigQuery dataset alongside the standard Stigg tables.

Stigg entity schema

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Setting up the integration

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Prerequisites

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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.

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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:
FieldDescription
HMAC Key Access IDThe HMAC key access ID used to access the GCS bucket
HMAC Key SecretThe HMAC key secret used to access the GCS bucket
GCS Bucket NameThe name of the GCS bucket that will be used in the integration
GCS Bucket PathThe directory path in the GCS bucket where data will be written
Project IDThe GCP project ID containing the target BigQuery dataset
Dataset locationThe location of your BigQuery dataset
Dataset IDThe default BigQuery Dataset ID used when the source does not specify a namespace
Service Account Key JSONThe Google Cloud Service Account Key in JSON format
3

Select entities to export

After entering your connection details, expand the Entities to export section to choose which entity groups to include in the sync. All groups are selected by default.See Exported entities for a description of each group.
4

Connect

Click Connect to BigQuery to complete the setup.

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Sync process and schedule

After setup, Stigg performs a full sync of all selected entities. Subsequent syncs are incremental, transferring only changes since the last run. Stigg syncs data to BigQuery daily at 12:00 AM UTC by default. You can configure a custom sync frequency during setup or from the BigQuery integration settings afterward.

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Manual sync

To trigger an immediate sync, open the BigQuery integration in Stigg and click Sync now.

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Sync history

The BigQuery integration page shows a log of all past and in-progress syncs, including status, start and end timestamps, and error details for failed runs. Use the status and date filters to find a specific sync.

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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.