- easy to integrate with current ecosystem ( data warehouse, dasboarding tool, SQL applications) -UI are modern and userfriendly -ML capabilties can identify a good porton of data issues

As a user who is also responsible for admininstering access and getting other users set up in Monte Carlo, my review covers both sides. Firstly, Monte Carlo makes it super simple for teams to get their data ingested which therefore reduces the time I need to spend walking them through the process. Once teams have completed their side of the set up, it only takes me 15 mins to create and set up a brand new team with the out-of-the-box monitors and set up alerting to their chosen Slack channel. Teams then often use the provided Monte Carlo documentation to go further, setting up custom monitors and sharing their experiences in our internal community channel. I've since had lots of positive stories from users describing how Monte Carlo caught issues immediately that would have previously festered for a good few days before being spotted. As a user, the flexibility with setting up new monitors is fantastic and it's easy to do. With some continued improvement we now only have useful alerts coming through to our channel which we can idenify and action straight away. The support Monte Carlo provide is great and really helps to make sure you're successful.

Ease of use, low or no code, however support for more sophisticated tests, anomaly detections, easy set up of alerts / notifications, api allowing integration with Collibra (data catalouge) to publish DPs SLIs (Service Level Integrations), and cherry on top - column level lineage of DB objects. Great customer support as well