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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 project selection combobox
2. Go to IAM and Admin > Roles
3. Click the Create Role button on top.
4. Fill in information as follows
   1. Title: Coalesce Quality Monitoring
   2. Description: Coalesce Quality Monitoring role
   3. Role launch stage: General Availability
   4. Assigned permissions:
   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. Confirm and save

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Create a service account

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

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Create a service account key

1. Open your newly created Service Account
2. Switch to Keys tab
3. Create a new JSON key
4. Store the newly created JSON key securely.

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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

You can see all your projects and the associated IDs by clicking the drop-down and looking at the ID column of the 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).