Data Observability for the Data Cloud

Monte Carlo makes it easy for data organizations powered by Snowflake to detect, resolve, and prevent data downtime and data quality issues before they impact the business, giving companies confidence in the reliability of their data and the products they power.

  • Fox
  • CNN
  • JetBlue
  • Opentable
  • Sonos
  • Jaguar Land Rover

100% table coverage, instantly

Get end-to-end data observability for your Snowflake data pipelines with a 20-minute, no-code implementation process.

Trusted data teams

Monte Carlo continuously monitors your Snowflake assets to enable your team to quickly detect and resolve data incidents as soon as they occur.

Higher data adoption

With greater data trust, Monte Carlo enables teams across your organization to adopt data products powered by Snowflake.

Know when data breaks, as soon as it happens

Monte Carlo’s ML-powered anomaly detection automatically monitors 100% of your Snowflake tables out of the box, and enables your data teams with opt-in monitors and monitors-as-code to track your most critical assets.

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Find root cause, fast

Monte Carlo gives teams a single pane of glass to investigate data issues—including automated field-level lineage across your Snowflake pipelines—drastically reducing time to resolution.

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Prevent data downtime

Monte Carlo gives your teams full visibility into your Snowflake pipelines and how they impact downstream reports and dashboards so they can make more informed development decisions.

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Related resources

2023: The state of data quality

Did you know that bad data impacts 31% of a company’s revenue? And that 74% of data engineers say data quality issues are surfaced first by stakeholders? These stats and more in our recent survey with Wakefield Research.

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3 simple steps for Snowflake cost optimization without getting too crazy.

Snowflake cost optimization efforts need to be right sized. Learn how to get the most savings with investing too much of your team’s time.

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Data testing vs. data quality monitoring vs. data observability: What's right for your team?

In the fight against bad data and broken pipelines, there are a few popular options. But what makes the most sense for your data quality needs? We’ve got the answers.

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