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Monte Carlo

End-to-end data observability platform for monitoring data quality and reliability. It integrates with MotherDuck for table monitoring as part of data quality and observability workflows.

How it works with MotherDuck​

Monte Carlo connects to MotherDuck for data observability workflows, including custom SQL monitors over MotherDuck tables.

Prerequisites​

  • A Monte Carlo account with access to the MotherDuck integration.
  • A MotherDuck account and database access for the objects you want to monitor.
  • A MotherDuck service token that can run the monitor queries.

Setup​

  1. In MotherDuck, create a service token for Monte Carlo.
  2. In Monte Carlo, add MotherDuck as a data source.
  3. Enter the MotherDuck connection details requested by Monte Carlo.
  4. Validate the connection.
  5. Create custom SQL monitors for the tables, freshness checks, or metrics you need to observe.

Authentication and configuration​

  • Use a dedicated token for Monte Carlo monitoring.
  • Grant access to the databases and schemas where monitor queries run.
  • Keep monitor queries scoped to the smallest useful result set.

Important notes​

  • Monte Carlo lists the MotherDuck integration as public preview in its documentation. Confirm current availability and support requirements with Monte Carlo before relying on it for production alerting.
  • Query complexity and result size affect monitor performance.

Use cases​

  • Monitor freshness or row-count expectations for MotherDuck tables.
  • Run custom SQL checks against curated analytics models.
  • Route MotherDuck data quality incidents into existing Monte Carlo notification workflows.

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