Product demo. 
What is data observability? 
What is a data mesh--and how not to mesh it up 
The ULTIMATE Guide To Data Lineage 
Observability across your modern data stack. Detect, alert, resolve, and prevent data incidents at scale.
Data and AI reliability. Delivered.
Data breaks. Monte Carlo ensures your team is the first to know and solve with end-to-end data observability.
Sick of "why is my data wrong" messages?
Data engineers: wouldn’t it be great if you could understand the freshness, volume, schema, and quality of your data? What if you were notified before stakeholders when your dashboards broke?
Tired of spending days resolving data quality issues?
Analysts: data quality issues drain resources, erode stakeholder trust, and can take hours to days to root cause and resolve. Wouldn’t it be nice if you had incident detection and resolution at your fingertips?
Done with products you can't trust?
Executives: did you know that bad data costs companies millions of dollars per year? Imagine a world in which you didn’t have to second guess the data powering your dashboards, products, and digital services.
End-to-end data observability.
Data observability
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Know when data breaks – as soon as it happens. Receive and triage alerts via Slack, Teams, JIRA, and other channels you already use.
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Identify the root cause and understand impact via field-level lineage and automated incident management tooling – all in a single UI.
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Prevent future data incidents by understanding your most critical data assets and setting custom rules at scale.
use Monte Carlo to build data trust.
“We have over 2,000 tables we need visibility into. Monte Carlo gives us the ability to understand data quality across these assets at scale.”
Trish Pham
Director of Analytics
“Combined with Snowflake’s powerful Data Cloud and Monte Carlo’s Data Observability Platform, we can resolve problems before they reach the business. My executives are happy and I can trust our data.”
Jacob Follis
VP of Analytics and Digital Transformation
“It’s really easy for us to propose and make big changes upstream in the data warehouse and know exactly what is going to be impacted by the change.”
Dylan Hughes
Senior Software Engineer
“Monte Carlo alerts are high quality. We don’t get many false alarms, which really helps build a culture of urgency to event management and response.”
Adam Woods
CEO
“We have 10% of the incidents we had a year ago.”
Daniel Rimon
Head of Data Engineering
