End-to-end coverage, instantly
Monte Carlo can be deployed in minutes, and immediately notifies specific data team owners as soon as data incidents occur.
End-to-end visibility, automated monitoring, and targeted notifications. All available in minutes.
Monte Carlo can be deployed in minutes, and immediately notifies specific data team owners as soon as data incidents occur.
In addition to data team owners, Monte Carlo notifies downstream users when data issues occur to prevent the use of critical dashboards until an incident is resolved.
Monte Carlo is SOC 2 Type 2 certified and monitors data at-rest, limiting compute cost by extracting only metadata, query logs, and aggregated statistics.
Monitoring and anomaly detection across your modern data stack + targeted notifications make for more productive and relaxed data teams.
Monte Carlo is deployed using no-code implementation and pre-built integrations across your cloud-native data stack, allowing for setup in 20 minutes with complete field lineage mapping within 24 hours. It’s that fast, but don’t just take our word for it.
Within minutes of deploying Monte Carlo, my team was up and running, and we had full visibility into our data pipelines, from ingestion in BigQuery to analytics in our Looker dashboards.
Monte Carlo’s machine learning-powered anomaly detection automatically establishes a baseline to evaluate freshness, distribution, volume, and schema changes within 2 weeks— without configuring or thresholding.
Within minutes, we were up and running with Monte Carlo and within days, the platform was uncovering critical schema and pipeline changes that would have impacted the business if left undetected.
For key data assets, your team can create additional opt-in monitors field health, dimension tracking, and JSON schema with just a few clicks, or deploy monitors-as-code with SQL rules and custom SLIs.
We wanted something that would effectively get this off the ground and running without us having to put in that effort. The schema, volume, and freshness checks that Monte Carlo offers delivers on that.
Related data issues are automatically grouped into a single notification to limit noise, and your team can control who is notified, including data team owners and downstream BI dashboard users, in the channel of their choice.
Monte Carlo’s monitoring feed to Slack gives me comfort that our data is healthy and everything’s working as designed. If something goes wrong, I know we’ll be the first to know and solve.
What Monte Carlo did, which was amazing in my mind…and basically without me setting up anything, they started listening and building anomaly detection and freshness metrics to all the tables and data sets that we have…suddenly I’m aware of problems I wasn’t aware of at all.
Detection is not enough. Empower your data teams to resolve data incidents in minutes, not days.
Use your favorite stack. Get a single view into data health across your data lakes, warehouses, orchestration and BI tools.
Customers like Choozle have reduced time-to-detection from days to minutes.