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Peace of mind through automated data monitoring
What do you like best about the product?
Monte Carlo has an exceptional out-of-the box monitoring capability which has helped us scale our data quality to thousands of tables with ease. Their UI is very intutive and the asset dashboard provides an unparalleled glance at how your data in the tables is developing. It has become part of my daily workflow.
Additionally, their customer support has been excellent!
Additionally, their customer support has been excellent!
What do you dislike about the product?
So far, I don't have any reasons to dislike the product. However, there are a few areas of improvements in the administration of users (i.e. domain-based access) which could be simpler.
What problems is the product solving and how is that benefiting you?
Anomaly detection within our tables with regard to the number of rows and the frequency of updates.
Circuit-breaking our pipelines in case of unhealthy data.
Incident management, such as keeping stakeholders up-to-date about the progress.
Circuit-breaking our pipelines in case of unhealthy data.
Incident management, such as keeping stakeholders up-to-date about the progress.
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Great Data observability tool.
What do you like best about the product?
1. Alerts for the data behaviour changes.
2. Supported us many times with anomalies in timely manner.
2. Supported us many times with anomalies in timely manner.
What do you dislike about the product?
1. Too many alerts some scenarios during non business days.
What problems is the product solving and how is that benefiting you?
On daily basis, MC tool monitor our tables and notify us.
Many times, MC helped us for Freshess, Volume and Schema chnages in our tables.
Many times, MC helped us for Freshess, Volume and Schema chnages in our tables.
Great data observability service!
What do you like best about the product?
Constant monitoring of our data platform on so many aspects, ease of use and flowy UI.
We use it on daily basis since its alerting solution is very versatile and persice.
We use it on daily basis since its alerting solution is very versatile and persice.
What do you dislike about the product?
In some cases its first AI generated threshold is inadectiute and causes data lags that causes us to miss it out. A human intervension will than resolve this issue.
What problems is the product solving and how is that benefiting you?
Monte Carlo solves a variaty of issues such as data integrity, data validation, error history, profound visablilly angles on our asests and amazing lineage that help us with impact analisys.
Simple to get going, great support from the MC team
What do you like best about the product?
As a data leader, it is great to see teams across the Tech and business domains are able to onboard, self-start and build data reliability into their day to day with relatively ease. The docs, training and support from the MC team is superb, which really takes the cost and effort out of my own limited resources. And this is having measurable impact in the quality of data across our estate thanks to the automated, self-learning nature of the platform.
What do you dislike about the product?
It's a stretch for a 'downside' but... perhaps the simplicity with which we can onboard new teams into the tool and get the basics up and running means that we don't need to have dedicated focused support for the platform, which may lead to a slight plateau in our ramp up into the more mature capabilities.
What problems is the product solving and how is that benefiting you?
driving greater reliability of our data across a federated data ownership landscape of teams who are constrained for capacity and do not have 'data' as their primary purpose in their day to day.
Montecarlo as a success for business monitoring
What do you like best about the product?
Monte Carlo helped us a lot in making sense of our data quality. It is a great tool to help with catching errors in our data sources before it is identified by our stakeholders.
What do you dislike about the product?
Some features were missing from the get-go, so it took a bit of back and forth with the support to have them implemented or having workarounds for them, but they have been amazing at it.
What problems is the product solving and how is that benefiting you?
One of the biggest challenges we faced was to identify quality and quantity errors in our data pipelines. We had to create custom monitors for some of our tables to prevent errors from propagating to the end-users. Fortunately, we found Montecarlo, which helped us in monitoring and alerting us whenever there was an issue with the data.
Great data monitoring and quality tool!
What do you like best about the product?
Automatically detect and flag data anomalies in real-time at scale
Accelerate triage and troubleshoot with rich context of data assets and lineage
Intuitive and user friendly interface
Accelerate triage and troubleshoot with rich context of data assets and lineage
Intuitive and user friendly interface
What do you dislike about the product?
Incident dashboard has no filter on audience
Could receive too many Alerts if not configered property
Could receive too many Alerts if not configered property
What problems is the product solving and how is that benefiting you?
MC expedites the identification and resolution of data incidents related to freshness, volume anomalies, and schema changes. It offers comprehensive context for assets, while its data lineage capabilities enable swift tracing of incidents to their root causes, facilitating efficient troubleshooting and minimizing downstream impacts on users
Unparalleled out-of-the-box observability and ease of integration
What do you like best about the product?
The best functionality for me were the out-of-the-box ML monitors on data volume and freshness. These are hard to set up manually and they have proved crucial to use uncovering the "unknown" unknowns issues.
What do you dislike about the product?
Some functionality would benefit from more flexibility in the setup. For example, data integration errors and weekly digest emails are always sent, but we would like to adjust if and who receives them.
What problems is the product solving and how is that benefiting you?
Low data quality, unreliable data sources.
Powerful data observability tool
What do you like best about the product?
I like that that it can integrate with various tools like Airflow, DBT, Slack and that allows the team to see a fuller picture of the data quality. I also l like that everything is documented properly and appreciate the reactiveness of the Monte Carlo support team in case of question on a potentially missing feature or just how the tool works.
What do you dislike about the product?
Sometimes, the amount of features proposed can be overwhelming, as well as the UI. The feeling is "a lot is going on and I'm not sure where to look at". If one is unfamiliar with the tool or the metrics it shows, it is easy to get lost. I see however, that several video tutorial are available online to help the user naviguate the tool. Also when creating monitors, the amount of settings can be overwhelming, especially at the beginning.
What problems is the product solving and how is that benefiting you?
It shows a bigger picture of the data quality, from the source to the reporting tables. We can make different people responsible for the data quality when anomalies show up. It helps also the data source owner to be aware of the quality of the data they provide the data team with.
Our data quality watchdog
What do you like best about the product?
The ability to swiftly detect unexpected behavior in our data tables. This real-time alerting capability provides invaluable peace of mind, allowing us, data-scientists, to proactively address anomalies before they escalate into larger issues.
What do you dislike about the product?
One aspect that could be improved is the occasional occurrence of false positives. While these are to be expected to some degree in any alerting system, reducing their frequency would make the overall user experience almost perfect.
What problems is the product solving and how is that benefiting you?
Monte Carlo helps us solve our big problem: making sure our data is trustworthy every day. It keeps an eye on our data tables all the time and alerts us if something doesn't seem right. This helps us keep our data reliable and make smart decisions confidently.
Moving from User Reported Incidents to mature Data Quality Monitoring
What do you like best about the product?
Monte Carlo helps us to notice most issues with our data in key pipelines before our users become aware. This led to better decision making and an increase of trust into the data and our team. The support from Monte Carlo starting with the well guided integration, and continuing today, helps us to get the most out of this product.
What do you dislike about the product?
Data Quality must be approached with care. Monta Carlo in an incredible partner to establish a metric driven adoption. This helps us to mature in the disciplin. The only thing I would wish for is an official terraform provider instead of the embedded Monitor as Code feature that supports a slightly different feature set.
What problems is the product solving and how is that benefiting you?
Monte Carlo is helping us to notice data issues before the users are becoming aware. This enables us to fix the issue or inform our users proactively. By learning from previous incidents we can adapt our monitors and continously improve.
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