Monte Carlo Data Observability Platform
Monte Carlo DataReviews from AWS customer
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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 is great data quality tool providing machine learning feature and nice SDK
What do you like best about the product?
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
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.
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.
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
Monte Carlo has been a good tool for data quality and observability
What do you like best about the product?
It helps us catch data issues proactively
What do you dislike about the product?
No problems so far in the use of this software
What problems is the product solving and how is that benefiting you?
It helps us catch data quality issues proactively, which leads to trusts from our user base.
A valuable tool for catching data and performance changes proactively
What do you like best about the product?
I like the customization options of the platform best. We have been able to leverage it as a business performance monitoring tool, in addition to data completeness. The possible use cases are numerous.
What do you dislike about the product?
The largest downside of using Monte Carlo is the learning curve. It took a decent amount of prompting to get our business team comfortable with setting up alerts and using within our daily flow. The amount of options, while helpful, yielded a slower learning curve.
What problems is the product solving and how is that benefiting you?
Flagging to us when we have issues with our data builds and alerting when we have significant unexpected changes we need to take a deeper look into.
A tool with potential, but hindered by limitations currently
What do you like best about the product?
Low code/no code monitors on tables, which makes it easy to set up. Custom SQL monitors are also fairly straightforward to set up.
Allows for synergies in cases where multiple teams are using the same table for different models.
Customer support is quick to respond and acts on feedback promptly.
Allows for synergies in cases where multiple teams are using the same table for different models.
Customer support is quick to respond and acts on feedback promptly.
What do you dislike about the product?
Investigation tools for errors are very limited or maybe not intuitive
No python support so the type of checks that can be created becomes limited as well.
Lack of transparency for the machine learning thresholds and how each sensitivity level is calculated.
Dashboards not as useful/intuitive compared to something like Salesforce.
No python support so the type of checks that can be created becomes limited as well.
Lack of transparency for the machine learning thresholds and how each sensitivity level is calculated.
Dashboards not as useful/intuitive compared to something like Salesforce.
What problems is the product solving and how is that benefiting you?
The biggest problem Monte Carlo solves is transparency of data quality standards that can be viewed by anyone in the organization. For instance, we already had data validation methods that existed before Monte Carlo, but since they were owned by the teams that created the models, there was not a lot of transparency as to what data validation checks were implemented and whether they are sufficient. Monte Carlo really helps with this and makes sure the data quality is up to standard for all of our tables.
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