Monte Carlo Data + AI Observability Platform
Monte Carlo DataReviews from AWS customer
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Good Overall, But Custom Metric Limitations Hold It Back
What do you like best about the product?
It's really easy to set up different kind of monitoring alerts.
What do you dislike about the product?
Custom metric is a bit limited if you wat to do comparisons between fields within the same table.
What problems is the product solving and how is that benefiting you?
It's really easy to set up different kind of monitoring alerts.
Proactive Data Reliability That Keeps Us Ahead
What do you like best about the product?
Monte Carlo has helped our team maintain a much better sense of data reliability, as issues and changes in the data are now alerted to us proactively, we now have the chance to get things fixed before stakeholders even notice, rather than being reactive to their tickets about something being broken.
What do you dislike about the product?
Out of the box, we were a little overloaded with alerts that didn't actually signify anything of importance leading to alert fatigue, luckily the customization options gave us the opportunity to remedy that
What problems is the product solving and how is that benefiting you?
Data Observability, Proactiveness
Effortless Setup and Seamless Integration with Outstanding Support
What do you like best about the product?
I appreciate how easy it is to set things up. The platform's capability to handle multiple use cases within a single system is very useful. Its integration with the tools we already use allows me to take advantage of alerting features directly within my daily workflow. The customer support and engagement from our Monte Carlo team has been fantastic.
What do you dislike about the product?
Some of the admin side of things can be difficult when managing the different types of monitors. Being able to see our holistic quality and manage them from one central place can be tricky sometimes.
What problems is the product solving and how is that benefiting you?
We use Monte Carlo to monitor and alert us to any issues that might be going on in our complex architecture. The goal for us is to never have an end user catch issues with our data, but we have proactively set monitors up to manage that in advance.
Effortless Use and Insightful Summaries
What do you like best about the product?
Easy to use, great root cause analysis and agentic summaries
What do you dislike about the product?
pricing structure and budgeting is difficult
What problems is the product solving and how is that benefiting you?
Proactive notification of issues in our data ecosystem enable us to get ahead of breaks before downstream users are aware.
Huge time saver for our team
What do you like best about the product?
I like that we don't have to write our own DQ rules from scratch and its organized in a user-friendly UI. The data quality dashboard is a very useful tool to show executives and prove the ROI for the software.
What do you dislike about the product?
It can be complicated and overwhelming to understand the process as a whole on what to monitor, when to alert and what priority to assign. The popularity score doesn't always match with what the business considers our most important data and using the key asset tag doesn't allow the granularity to adjust how important an asset is. The AI features could use some work as they often offer suggestions that are not entirely helpful.
What problems is the product solving and how is that benefiting you?
The ability to test data quality in several dimensions on our bronze and gold layers without having to manually do this in Snowflake is a huge time savings for our team. The proactive monitoring has helped us catch data development errors before it reaches our end user. To have this summarized in a dashboard with an overall data quality score is a very helpful benchmark.
Effortless Data Monitoring with Monte Carlo
What do you like best about the product?
I like how Monte Carlo is very easy to set up and truly plug and play. It's super easy to connect to our systems and get alerts set up.
What do you dislike about the product?
I would like Monte Carlo to recommend which alerts to add from a business perspective.
What problems is the product solving and how is that benefiting you?
Monte Carlo helps me detect data anomalies in real-time. It's plug and play, making it very easy to set up and connect with our systems to get alerts quickly.
Easy to Use with Helpful Support, But Needs More Advanced Features
What do you like best about the product?
It's easy to use & setup. Customer support button is easy to find. There seem to be a decent number of features.
What do you dislike about the product?
There could be more advanced features and the ease of integration could be better.
What problems is the product solving and how is that benefiting you?
We are currently facing data quality challenges, including difficulties in identifying duplicates and ensuring observability. This is largely because, as a team, we have not yet established clear standards.
Turnkey Anomaly Detection with Stakeholder-Friendly UI
What do you like best about the product?
turnkey anomaly detection, and a UI for stakeholders to log in to.
What do you dislike about the product?
It's been tough getting people to adopt it, and while some of the "just monitor all the columns" are helpful, its tough to exclude problem columns.
What problems is the product solving and how is that benefiting you?
MC has helped us with trust - we have way better visibility into the state of our lake and whether users can trust the data.
Advanced Data Observability with Easy Setup
What do you like best about the product?
I like Monte Carlo's advanced feature in data observability, which comes with useful pre-defined tools like freshness and volume monitor. I also appreciate the ability to customize them with custom SQL. The freshness monitor helps us ensure we receive data from our upstream/source systems and our downstream data products are refreshed as expected. If not, we get alerted, allowing us to troubleshoot and perform fixes promptly. Setting up Monte Carlo was easy with the official documentation, using the Monitor-as-code method with YAML configurations, which is helpful for developers to maintain in a Git repository.
What do you dislike about the product?
I wish there was more customization with the Monte Carlo alerts to write our custom messages, so that when they are sent to stakeholders like data product owners or source system owners, they can get better context of the alert.
What problems is the product solving and how is that benefiting you?
Monte Carlo helps us monitor, identify, manage, and fix data anomalies. It ensures our data is fresh by alerting us if data from upstream sources isn't refreshed, allowing us to troubleshoot quickly.
Alert Tracking and Efficient Connections
What do you like best about the product?
I like the tracking of alerts with different means and the ease of being able to connect more applications. In day-to-day use, alerts are used with metadata and other queries that allow for customizing the rules.
What do you dislike about the product?
The format of the alert history can be improved when viewing them and the summary of impacted tables.
What problems is the product solving and how is that benefiting you?
With Monte Carlo, I track the quality rules in our data lake and receive customizable alerts. This allows me to connect more applications easily and monitor through metadata and custom queries.
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