Find and fix the root cause, fast

Automated field-level lineage, workflow tools, and all the context your team needs to triage and resolve incidents quickly. All in one place.

Automated data lineage tool Monte Carlo
Red Ventures
Unified platform

Unified platform

Monte Carlo enables your team to centralize data quality operations in one place by consolidating all the root cause analysis and workflow tools that your team needs.

Faster time-to-resolution

Faster time-to-resolution

With incident resolution at your fingertips, you can be at ease and build data trust across your organization.



Whether your goal is to reduce TTR, onboard new hires, or enable every data engineer to resolve incidents, Monte Carlo’s intuitive UI makes it possible.

Centralized data incident resolution

Faster time-to-resolution is enabled with automated lineage, impact radius assessment, workflow tools, and the context your teams need—all in one platform.

Automated field-level lineage

Within 24 hours of deployment, Monte Carlo equips your team with complete and up-to-date field lineage to fully understand upstream sources and downstream dependencies. That’s right, end-to-end data visibility in less than one day.

See demo

Monte Carlo ensures that we’re on top of any data fire drills the moment they arise, before they impact the business.

Pamela Dalal,
Head of Data
Automated field-level lineage

Impact radius assessment

As soon as your data team is notified of an incident, they can immediately triage by understanding who and which reports were impacted. Need the details? Just scroll or click.

See in action

With Monte Carlo, my team is the first to know when data breaks so that we can manage that incident lifecycle through PagerDuty, in turn allowing us to prevent and resolve data downtime before it impacts the business.

Manu Raj,
Senior Director of Data Platform and Analytics
Impact radius assessment

Workflow tools

Data reliability only happens when you’re 
able to operationalize; your data team can use 
Monte Carlo to set severity levels, assign 
owners, and keep your stakeholders apprised 
of status so they can trust their mission-critical reports.

Learn more

Monte Carlo’s monitoring feed to Slack gives me comfort that our data is healthy and everything’s working as designed. And on days where something goes wrong, I know my team will be the first to know and that we’ll be in command of the situation.

Suvayan Roy,
Senior Product Manager
Workflow tools

Root cause analysis

Data breaks. When it happens, it’s critical that your team can assess the incident timeline, view exactly when the freshness, distribution, or volume anomaly occurred, access query and orchestration error logs, and trace the issue upstream and downstream—all in one place, and across your modern data stack.

See in action

You look at the incident, and then all in one place you are able to see everything, like upstream and downstream dependencies and what was the root cause, right down to the piece of code.

Satish Rane,
Head of Data Engineering
Root cause analysis

The self-service capabilities of data observability helped build back trust in data, as users were seeing us in action: going from a red alert to a blue ‘work-in-progress’ to ‘resolved’ in green. They knew who was accountable, they knew the teams were working on it, and everything became crystal clear.

Gopi Krishnamurthy, Director of Engineering
Read their story
Latest release: Circuit breakers

Latest release: Circuit breakers

For the first time, data teams can automatically stop broken data pipelines before bad data impacts the business.

Press release
End-to-end visibility

End-to-end visibility

Use your favorite stack. Get a single view into data health across your data lakes, warehouses, orchestration and BI tools.

Maximize the value of your data stack

Maximize the value of your data stack

Rich insights enable your team to improve data products and make better infrastructure investment decisions.


Ready to set a company record for time-to-resolution?

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