1. the ease of setting up and understanding the monitors 2. Great variety of audiences and the ability to configure custom messages that includes elements from your actual query 3. The observability part is extremely powerfull. It observed all irregularities that were reported by users in ServiceNow plus an additional set of findings 4. It's good to see that Monte Carlo develops in an iterative way. You see the application continously changing, mostly for the better while the basic functionality stays in plays.

wie sich das maschinelle Lernen entwickelt, wenn mehr Informationen bereitgestellt werden. die Abstammung

Monte Carlo is very easy to onboard and user-friendly. Setting up data quality monitors is straightforward, allowing us to detect problems right away in case of any breaches. Alerts can be sent to respective Slack channels, making the appropriate people aware. Since adopting Monte Carlo, the data quality governance capabilities in our company have increased tremendously!