Monte Carlo Data + AI Observability Platform
Monte Carlo DataReviews from AWS customer
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Monte Carlo is a good tool and save us a lot of time to automatically detect data anomalies.
What do you like best about the product?
I like the automated detection of data anomalies the most.
What do you dislike about the product?
Sometimes, the alerts do not come at real time and they can come a few hours/days later than the actual outage.
What problems is the product solving and how is that benefiting you?
Monte Carlo brought more data observability and quality issues on our datasets.
user friendly and ease of use
What do you like best about the product?
Automated alerts, AI based quality control, User interface is easy to understand, has all the features and functionality that are needed for data quality checks.
What do you dislike about the product?
Sample use cases within the tool to help user understand what all monitors they can create.
What problems is the product solving and how is that benefiting you?
data quality checks to ensure data integrity and accuracy is maintained.
Great observability tool for data engineers, analysts, scientists, and product owners!
What do you like best about the product?
Low-code, no-code solution
The MC platform is very user friendly. Getting familiar to the app is not too difficult, and a lot of the built-in functionality is great!
The MC platform is very user friendly. Getting familiar to the app is not too difficult, and a lot of the built-in functionality is great!
What do you dislike about the product?
One thing I hope that Monte Carlo can implement is the feature for "starring" your favorite monitors/alerts/dashboards. This would make it much easier to get what you are exactly looking for rather than filtering down to your assets.
What problems is the product solving and how is that benefiting you?
Monte Carlo is helping detect anomalies within our data through the different monitors and alerts. I really like how a lot of the core ones for data quality are built in (Freshness, Volume), and the ability to create custom monitors helps a lot. Monte Carlo is also helping analyze which queries we execute are more expensive and compute-intensive. This helps us find ways to optimize our own performance.
Monte Carlo
What do you like best about the product?
Helpful to keep track of data inconsistencies
What do you dislike about the product?
the interface could be more user friendly
What problems is the product solving and how is that benefiting you?
Data discrepancies in our back end systems
Great Experience!
What do you like best about the product?
Monte Carlo makes it easy to catch and resolve data issues before they impact stakeholders. The automated data quality monitoring, lineage visibility, and alerting help us identify root causes quickly. The integration process was smooth, and the UI is intuitive enough that both technical and non-technical users can navigate it with ease. Their customer support team is responsive and genuinely helpful, which makes onboarding and ongoing use even better.
What do you dislike about the product?
Sometimes the initial alert volume can be high until fine-tuned, which may feel overwhelming for new users. While integrations are generally strong, a few niche connectors still require manual workarounds. Pricing can also feel steep for smaller teams, though the value is there once implemented.
What problems is the product solving and how is that benefiting you?
Monte Carlo helps us detect and fix data quality issues in real time, so bad data doesn’t make it to reports or dashboards. It automatically monitors pipelines, identifies schema changes or anomalies, and shows clear lineage to trace the root cause. This saves hours of manual investigation, improves trust in our data, and reduces the risk of decision-making based on inaccurate information.
Great for Data Engineers, not that much for other roles
What do you like best about the product?
I like the fact that everything is well integrated with other systems, such as Snowflake or PowerBI
What do you dislike about the product?
It is not very user friendly in comparison to some competitors
What problems is the product solving and how is that benefiting you?
It helps a lot with landing issues from Engineering teams
Monte Carlo keeps adding new features and upgrading, is great data quality tool with AI features
What do you like best about the product?
Support team is great and very helpful. Threshold can be determined by machine learning, SDK is easy to use for developers.
What do you dislike about the product?
Some API's document is not very detailed. When new feature roll out, it's not working for the first time.
What problems is the product solving and how is that benefiting you?
I can create different type of monitors to monitor data quality, data volume, job status etc, discover issue. I also use SDK/API to create datamart and do analysis.
Monte Carlo Review
What do you like best about the product?
The flexibility and getting timely and reliable alerts for Volume, Schema and Freshness is useful. Able to tune the model is great.
What do you dislike about the product?
Not dislike, but couple of things that can be better:
1) Dashboards can be better in providing more actionable insights like most frequently failing tables or top 5 failing tables, under which schema, failing for what reason, frequently failing monitors, etc
2) It would be great if any updates made on alerts in Monte Carlo can flow into ServiceNow incidents
3) Additional integrations with files would be great, like if a file has not arrived, etc.
4) If we can have the model tuned for alerts much sooner than 2 weeks would be a welcome move.
5) Conducting any workshops on a sandbox environment for teams would help engage more teammates to understand and gets on with Monte Carlo
1) Dashboards can be better in providing more actionable insights like most frequently failing tables or top 5 failing tables, under which schema, failing for what reason, frequently failing monitors, etc
2) It would be great if any updates made on alerts in Monte Carlo can flow into ServiceNow incidents
3) Additional integrations with files would be great, like if a file has not arrived, etc.
4) If we can have the model tuned for alerts much sooner than 2 weeks would be a welcome move.
5) Conducting any workshops on a sandbox environment for teams would help engage more teammates to understand and gets on with Monte Carlo
What problems is the product solving and how is that benefiting you?
Issues with data quality
Monte Carlo is best-in-class, especially for analytics engineers
What do you like best about the product?
The troubleshooting agent (in preview) has been a particular stand-out. Other than that, I'd say that the customization of alerts appearing in places like Slack is my favorite.
What do you dislike about the product?
The UI is very clunky and the pricing models aren't the most cost-effective.
What problems is the product solving and how is that benefiting you?
Monte Carlo helps with monitoring that our other tools don't address - particularly testing and monitoring our source data that comes from a variety of sources. It allows us to stand up testing for those in a unified and consistent manner. This allows our teams to focus on other technical work.
Makes it very easy to detect issues and stale data
What do you like best about the product?
The machine learning model. It is a good with finding anomalies
What do you dislike about the product?
How too sensitive it sometimes can be. It goes off sometimes too often
What problems is the product solving and how is that benefiting you?
Stale data issue
Anomalies
freshness
Anomalies
freshness
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