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// stage.quality.preview

// stage.quality.checks

Quality checks on every run

Bruin executes all of your quality checks immediately after your transformation logic, allowing you to ensure the data is accurate after every execution.

Multiple platforms: Bruin supports all major data warehouses, databases, and query engines.
Built on open-source: Bruin's quality engine is part of the open-source Bruin CLI, allowing you to run everything locally.
Built-in checks: Bruin supports a variety of built-in quality checks, such as not_null, accepted_values, and more.
Custom checks: Going beyond the built-in checks, Bruin allows you to define custom quality checks in SQL.

// stage.quality.pipeline

End-to-end quality at every step

Bruin's built-in data quality capabilities are designed to be executed at every step of the pipeline: ingestion, transformation, reverse ETL and more. Make sure the data is accurate at every step.

Blocking by default check.01: Quality checks are designed to be treated as gates, meaning that if a check fails, the pipeline will not proceed.
Non-blocking as optional check.02: If you have long-running checks that are optional, you can mark them as non-blocking, allowing the pipeline to proceed even if the check fails.
Templating in quality checks check.03: Bruin supports templating in quality checks, meaning that you can use variables in your checks, and run checks only for incremental periods.
Automated alerting check.04: Failing quality checks will automatically send alerts to the configured channels, ensuring that you are always aware of the data quality issues.

raw.users.yaml

name: raw.users
type: ingestr

parameters:
  source_connection: postgresql
  source_table: 'public.users'
  destination: bigquery

columns:

  # Define columns along with their quality checks
  - name: status
    checks:
      - name: not_null
      - name: accepted_values
        values:
          - active
          - inactive
          - deleted

# You can also define custom quality checks in SQL        
custom_checks:
  - name: new user count is greater than 1000
    query: |
      SELECT COUNT(*) > 1000 
      FROM raw.users 
      WHERE status = 'active' 
        AND created_at BETWEEN "{{start_date}}" AND "{{end_date}}"