Documentation Index

Fetch the complete documentation index at: https://docs.synq.io/llms.txt

Use this file to discover all available pages before exploring further.

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Data we collect

For the automated data anomaly testing, we collect the following:

• Number of rows in every table in the monitored dataset(s)
• Timestamp of the last change of data in all tables in the monitored dataset(s)

To provide out-of-the-box monitors for volume and freshness, we don’t require access to your actual data. For custom monitors, however, access to query your raw data is required. Permission overview:

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Setup BigQuery access

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Create a dedicated Coalesce Quality role

1. Select the project with your BigQuery instance in the project picker.
2. Go to IAM and Admin → Roles → Create Role.
3. Fill in:
   • Title: Coalesce Quality Monitoring
   • Description: Coalesce Quality Monitoring role
   • Role launch stage: General Availability
4. Click Add permissions and add:
   bigquery.datasets.get
   bigquery.datasets.getIamPolicy
   bigquery.jobs.create
   bigquery.jobs.get
   bigquery.jobs.list
   bigquery.jobs.listAll
   bigquery.tables.get
   bigquery.tables.getData
   bigquery.tables.list
   bigquery.routines.get
   bigquery.routines.list
   resourcemanager.projects.get
   
   
5. Click Create.

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Create a service account

1. Go to IAM and Admin → Service Accounts → Create Service Account.
2. Fill in:
   • Service account name: synq-monitoring
   • Service account description: Coalesce Quality Monitoring Service Account
   
3. Click Create and continue.
4. In section Grant this service account access to the project, select the previously created Coalesce Quality Monitoring role, then click Done.

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Create a service account key

1. Open your newly created service account and switch to the Keys tab.
2. Click Add key → Create new key, choose JSON, and click Create.
   
3. Store the downloaded JSON key file securely.

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Personal access (user OAuth)

In addition to the workspace service account above, you can let each Coalesce Quality member authenticate as themselves against BigQuery. Queries then run under the member’s own Google identity and respect the IAM grants on that user. See Data Warehouse Access for the full model and when to enable it. To enable personal access, a Google Cloud admin creates a single OAuth 2.0 Client ID once, then pastes the client ID and secret into the BigQuery integration’s edit page in Coalesce Quality.

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Configure branding

Skip this step if your project’s Google Auth Platform is already configured.

1. In the Google Cloud console for the project that will host the OAuth app, go to Google Auth Platform → Branding.
2. Fill in the app name (e.g. Coalesce Quality), user support email, and developer contact.
   
3. Save.

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Choose the audience

1. Go to Google Auth Platform → Audience.
2. User type: pick Internal if every Coalesce Quality member has a Google account in your Workspace organisation, otherwise External.

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Create the OAuth client

1. Go to Google Auth Platform → Clients → Create client.
2. Application type: Web application.
3. Name: e.g. Coalesce Quality.
4. Under Authorised redirect URIs, add the URI(s) for the Coalesce Quality region(s) your members use, with no trailing slash:
   • EU: https://app.synq.io/auth/dwh-oauth/callback
   • US: https://app.us.synq.io/auth/dwh-oauth/callback
   
5. Click Create. Copy the Client ID and Client secret.

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Enable the BigQuery API

In the same project, go to APIs & Services → Library, search for BigQuery API, and click Enable (already enabled if you scrape BigQuery from this project).

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Paste credentials into Coalesce Quality

In Settings → Integrations → (your BigQuery integration) → Warehouse access → Personal credentials, paste the Client ID and Client secret. Members will then see this BigQuery integration listed under Settings → Warehouse access → My credentials and can connect their own Google account.

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Network Configuration

Once you’ve successfully completed these steps, input the following data in the platform.

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Input data in the Coalesce Quality UI

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Integration name

For example BigQuery

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Project ID

Open the project picker at the top of the Google Cloud console and copy the ID column value for your project.

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Service account key

The content of the JSON file you created earlier in the guide

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Region

Location of your BigQuery instance (typically US or EU)

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Blacklisted datasets (optional)

Comma-separated list of dataset name patterns to exclude from ingestion. Use * to match any string, e.g. dbt_pr_*.

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Datasets (optional)

Comma-separated list of dataset names to scrape explicitly (e.g. analytics, mart_core). When set, only these datasets are queried and the service account does not need the project-level bigquery.datasets.list permission — this lets you grant the Coalesce Quality Monitoring role on individual datasets instead of the whole project. Leave empty to auto-discover every visible dataset in the project.

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Audit table FQN (optional)

Fully-qualified table name (e.g. my-project.analytics.synq_sql_test__audit) where Coalesce Quality writes SQL test execution results. The integration creates the table automatically if it does not yet exist. Leave empty if you do not run SQL tests. Using this field requires two extra permissions on the target dataset that are not in the default role above: bigquery.tables.create and bigquery.tables.updateData. Add them to the Coalesce Quality Monitoring role (or grant them just on the audit dataset) before enabling the feature.

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Fetch query logs (recommended)

Enables ingestion of query history from INFORMATION_SCHEMA.JOBS, which powers anomaly-monitor training, data-usage insights, unused-table detection, and cost signals. Expect a small additional query cost (typically a few dollars per month).