Monte Carlo Data + AI Observability Platform
Monte Carlo DataReviews from AWS customer
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Great post production data quality tool.
What do you like best about the product?
Full confidence about my data quality. After applying monitors on top of my datasets, I can rest assure that the data is correct and accessible.
Moreover, our customer support is good when needde.
Moreover, our customer support is good when needde.
What do you dislike about the product?
Slack notifications payload design - In case I want to create a custom monitor and send an "advanced" and more informative payload, it's not that easy and accessible.
What problems is the product solving and how is that benefiting you?
Data freshness - be aware of latency so we'll be able to notify our data consumers. Data anomalies, Schema changes, nulls ext. - Monte helps us be in control over our hundreds of data assets, so we can focus on the most needed tasks and bugs.
Moreover - The slack integration with the user-set statuses helps us understand which incidents is being taken care of already, and which still requires our attention.
Moreover - The slack integration with the user-set statuses helps us understand which incidents is being taken care of already, and which still requires our attention.
End-to-end easy visibility of the data
What do you like best about the product?
Monte Carlo helps us to identify any potential inconsistency in the data framework at a quick glance. It helps flag cases that would be difficult to identify otherwise
What do you dislike about the product?
No major things, though after using other software to alert on inconsistencies with the business, I think that would be usefult that MC allows notification to contain tables with the hits that have created the alert.
It is useful for the business to easily check the alert driver and some columns that may be useful for them
It is useful for the business to easily check the alert driver and some columns that may be useful for them
What problems is the product solving and how is that benefiting you?
Analyse big pipelines end to end
Monte Carlo helps us in Data Observability
What do you like best about the product?
We get alerts from Monte Carlo as per schema change, null pct change, etc, which gives us insights of data changes of important tables.
What do you dislike about the product?
Sometimes we receive alerts of tables not in our domain.
What problems is the product solving and how is that benefiting you?
Monte Carlo helps monitor changes of each specified attribute, which is almost impossible to do manually.
Automated and evolving insights on your Data Mesh - Data Products
What do you like best about the product?
They are innovative and every month, I'm getting a new feature on my dashboard. The intergation with other Data Engineering tools is great. Monitoring as a Code or UI based monitoring management is very easy. The team is very responsive in term of customer support either for new feature or bug fixes.
What do you dislike about the product?
The naming conventions are a bit un orthodox or confusing at times.
I'm waiting for more evolved dashboarding features.
I'm waiting for more evolved dashboarding features.
What problems is the product solving and how is that benefiting you?
I'm able to monitor data availablity and qulaity matrics very easily. Do get alerts and automated management on the same.
- It's help me generate/capture SLIs on My Data Products and share them with stakeholders and potential consumers of my data.
- It's help me generate/capture SLIs on My Data Products and share them with stakeholders and potential consumers of my data.
Monte Carlo is a Game Changer
What do you like best about the product?
Monte Carlo is a tool that is easy to implement, use, and drive value through for users across our organization. In our case, we started seeing value during the first week of our proof of concept (POC) period and have continued to generate more value since!
A big reason for this is that Monte Carlo not only helps identify a data anomaly faster than we had ben able to before, but also quickly enables users to understand the context and impact of the event. Lineage, Impact Analysis, Correlation Analysis, and integrations with various tools helps you put the alert into context and also resolve the issue much faster than an out of context alert.
Outside of the abilities of the core product, the support team is top notch and actively takes feedback to enhance the product. The team is truly customer first. We have never had a customer support request fall off the radar and they are always proactive in making sure we find the best solution for our needs.
Lastly, Monte Carlo is a tool designed for scale and the product is centered around making it easy for an organization to standup up a data quality program (with support activities) all through the tool.
A big reason for this is that Monte Carlo not only helps identify a data anomaly faster than we had ben able to before, but also quickly enables users to understand the context and impact of the event. Lineage, Impact Analysis, Correlation Analysis, and integrations with various tools helps you put the alert into context and also resolve the issue much faster than an out of context alert.
Outside of the abilities of the core product, the support team is top notch and actively takes feedback to enhance the product. The team is truly customer first. We have never had a customer support request fall off the radar and they are always proactive in making sure we find the best solution for our needs.
Lastly, Monte Carlo is a tool designed for scale and the product is centered around making it easy for an organization to standup up a data quality program (with support activities) all through the tool.
What do you dislike about the product?
I think there are still some enhancements actively being made to help users more easily administer the tool, but overall, there are not any big dislikes about Monte Carlo.
What problems is the product solving and how is that benefiting you?
Monte Carlo has given us end to end observaiblity of key data pipelines that power the core of our business. Data trust is a key factor in any analysis and Monte Carlo has increasingly enabled us to trust our data and quickly take action when things begin to look off.
Montecarlo review
What do you like best about the product?
- 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
-UI are modern and userfriendly
-ML capabilties can identify a good porton of data issues
What do you dislike about the product?
we had some points in the past months but the team is addressing them rapidly
What problems is the product solving and how is that benefiting you?
-Issues on data pipeline
-Proactive data monitoring
-Proactive data monitoring
The ultimate guard for data issues
What do you like best about the product?
Good response time from their support team.
The support team really tries to understand our use cases.
Automatic monitors have been super useful for data engineering purposes.
Custom SQL rules look promising for anomaly detection.
dbt integration has been very useful for the analytics engineering team.
We appreciate the possibility to test beta features, like the Performance tab, which has been very helpful to us in a couple of projects.
We use it daily to review incidents and document.
The support team really tries to understand our use cases.
Automatic monitors have been super useful for data engineering purposes.
Custom SQL rules look promising for anomaly detection.
dbt integration has been very useful for the analytics engineering team.
We appreciate the possibility to test beta features, like the Performance tab, which has been very helpful to us in a couple of projects.
We use it daily to review incidents and document.
What do you dislike about the product?
Our BI tool, Metabase, is currently not supported.
What problems is the product solving and how is that benefiting you?
- Monitoring of data engineering pipelines. Monte Carlo has proven that logging tools such as Datadog are not enough for data engineers.
- Performance monitoring for analytics engineering.
- Performance monitoring for analytics engineering.
Game changer for the observability of a data platform
What do you like best about the product?
The out-of-the-box monitors based on ML.
What do you dislike about the product?
Still room of improvement in terms of UI and time to reflect in the interface changes applied to the configuration of assets and monitors.
What problems is the product solving and how is that benefiting you?
Applying data monitors at scale
Monte Carlo: an experience end-to-end for monitoring data quality
What do you like best about the product?
As a tool:
- it is straightforward to set up / implement with the out-of-the-box connectors
- great out-of-the-box monitors / visualization
- great incident management features
- the UI is very user-friendly
And a great customer support team!!
- it is straightforward to set up / implement with the out-of-the-box connectors
- great out-of-the-box monitors / visualization
- great incident management features
- the UI is very user-friendly
And a great customer support team!!
What do you dislike about the product?
- Cannot detect an incident before a code is pushing into production: only when it's running in production
- We tried to implement a connection between a SQL Server and Monte Carlo and the connection between Monte Carlo and this on-premise instance wasn't the easiest to manage by knowing that the features proposed by this connector are quite limited
- We tried to implement a connection between a SQL Server and Monte Carlo and the connection between Monte Carlo and this on-premise instance wasn't the easiest to manage by knowing that the features proposed by this connector are quite limited
What problems is the product solving and how is that benefiting you?
To detect incidents in real-time and to be pro-active in the incidents solving
We use MC to monitor a significant number of our tables.
What do you like best about the product?
Good connectivity between different tools e.g. slack, links go directly to GCP BQ etc
What do you dislike about the product?
We have many slack updates set up and the slack updates provide significantly less detail than the images produced on the MC incident page itself
What problems is the product solving and how is that benefiting you?
Allowing us to let our processes run automatically without having to frequently check our tables for data quality. Issues in our source data or processes are identified and the alert is sounded before these issues can reach the business
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