BACK

Monte Carlo brings end-to-end observability and lineage features into your modern data stack. Combining Prefect with Monte Carlo allows you to track data lineage, as well as to monitor data freshness, completeness, data volume and schema changes.

Gain end-to-end observability of your data platform

While Prefect is able to orchestrate the execution of your flows and tasks and govern their states, Monte Carlo can track additional metadata based on rules that you define. By combining both tools, you get highly granular end-to-end observability into everything that happens in your data pipelines (Prefect) and in your data (Monte Carlo).

Prevent broken data pipelines

Prefect provides building blocks that let you build robust data pipelines, from advanced scheduling, retries and custom Automations to providing granular visibility into your distributed computations on Dask. Adding Monte Carlo to the mix allows you to prevent the "good pipelines, bad data" problem.

Get automated data catalog and lineage

Prefect is able to tell a lot about your data pipelines, but due to the hybrid execution model, Prefect doesn't store any of your code or data. Monte Carlo allows to fill that gap by collecting metadata about your in-warehouse data operations and providing automated lineage information.

"As systems become increasingly complex and companies ingest more and more data, the opportunity for data downtime only grows, costing organizations valuable time and resources that could otherwise be spent innovating. Monte Carlo and Prefect's integration and partnership ensures that data teams avoid these operational issues and achieve unprecedented control and visibility into the health of their data, at each stage of the pipeline."

Barr Moses / CEO and Co-Founder of Monte Carlo

Integrate with Monte Carlo

Monte Carlo brings end-to-end observability and lineage features into your modern data stack. Combining Prefect with Monte Carlo allows you to track data lineage, as well as to monitor data freshness, completeness, data volume and schema changes.

  • End-to-end observability of your data platform
  • Prevent broken data pipelines
  • Get automated data catalog and lineage