Monte Carlo

Monte Carlo offers a data observability platform that helps organizations monitor and ensure the reliability of their data assets. The platform uses machine learning to automatically detect and prevent data quality issues, known as data downtime - periods when data is missing, incomplete, or inaccurate. It monitors five key pillars of data observability: freshness, volume, schema, quality, and lineage. The platform connects securely to data warehouses, lakes, and BI tools, extracting only metadata, logs and statistics without storing actual data. Using ML-powered anomaly detection, Monte Carlo assigns importance scores to tables and automatically identifies abnormalities across the data stack. The platform includes automated monitoring, alerting, and root cause analysis capabilities along with field and table lineage tools to track data dependencies and identify sources of issues. As of 2023, data teams using Monte Carlo reported a 88% reduction in data downtime, with one company saving 44 hours per week previously spent troubleshooting data pipelines.