Monte Carlo

Monte Carlo is a platform for end-to-end data observability – a term coined by its CEO – to help organizations monitor abnormal patterns in their data. Data observability refers to an organization’s ability to understand its data by monitoring its volume and quality as it moves through data pipelines. Similar to how observability helps DevOps teams monitor system health, data observability does the same for DataOps teams. It helps them automate monitoring, alerts, and issue handling to keep track of data health. This method flags inaccurate data before it flows downstream into systems like data warehouses and AI models.