Monte Carlo Data Observability Platform
Monte Carlo DataReviews from AWS customer
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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.
Data Monitoring made easy
What do you like best about the product?
1. Monte Carlo pro-actively catches data incidents that would have gone unnoticed
2. Seamless integration with other Data Tools makes it easier to track impact across platforms
3. The documentation provided guides you through the tool
4. The toolkit of checks Monte Carlo can perform makes it the leading tool
2. Seamless integration with other Data Tools makes it easier to track impact across platforms
3. The documentation provided guides you through the tool
4. The toolkit of checks Monte Carlo can perform makes it the leading tool
What do you dislike about the product?
1. Non-technical users have a bit of a learning curve
2. Out-of-the-box checks could lead to alert fatigue if unchecked
2. Out-of-the-box checks could lead to alert fatigue if unchecked
What problems is the product solving and how is that benefiting you?
Tracking breaking changes introduced by code (schema changes)
Data Irregularities: Data Volume, Update Frequency
Custom SQL Checks provide flexibility
Keeping other data-related functions in the loop for the data they own
Data Irregularities: Data Volume, Update Frequency
Custom SQL Checks provide flexibility
Keeping other data-related functions in the loop for the data they own
Great Tool for Data Observability
What do you like best about the product?
The incident feature is what I like the best. Its ability to provide real-time alerts for anomalies or issues in data ensures data reliability and integrity. This proactive approach saves valuable time and resources by quickly identifying and resolving issues before they impact operations.
What do you dislike about the product?
The UI could be more intuitive and user-friendly. It sometimes feels a bit cluttered and could benefit from a cleaner design to enhance the overall user experience.
What problems is the product solving and how is that benefiting you?
Its real-time anomaly detection saves me time.
Not too bad
What do you like best about the product?
Web interface, Rule creation, Snowflake connectivity set up
What do you dislike about the product?
Mostly, it hard to find usuful information about triggered rule
What problems is the product solving and how is that benefiting you?
Thanks to simple rules it is easy to manage snowflake monitoring across multiple geo sites.
Great Data Observability & Quality tool !
What do you like best about the product?
Montecarlo assures us that data is fresh and accurate. Montecarlo notifies us on Slack when there is an incident. We were able to spot data sync issues thanks to Montecarlo. We can create custom monitors to monitor a specific rule. Montecarlo is easy to use and the product is always evolving, adding new features. We can monitor easily the dbt runtimes for each model, the volume of queries on our database ... Also the MC team is very available and is quickly answering to our questions. I'm using MC every day and it makes my work easier !
What do you dislike about the product?
If I had to say something it would be the fact that sometimes an incident is a group of incidents on different tables, and that sometimes the incidents are not related, so we should not have only one status, but one status by incident. Also MC is sometimes mixing up two tables with the same name but in different schemas. Also the lineage feature doesn't seems to work from time to time.
What problems is the product solving and how is that benefiting you?
Monitor the quality, accuracy, freshness of the data for us. Lot of time gained and serenity.
My Experience of using MonteCarlo as a Data Engineer
What do you like best about the product?
Catching unusual variations in table over time
What do you dislike about the product?
False positive in volume monitor.
Time needed to set-up custom monitors
Time needed to set-up custom monitors
What problems is the product solving and how is that benefiting you?
Catching errors in tables and making sure our tables are always reliable
Monte Carlo Review
What do you like best about the product?
- Easy to get an end-to-end view of data flows in our warehouse
- Great on boarding support
- Each user in our company can use it
- New features appearing
- Some support for Data products
- Great on boarding support
- Each user in our company can use it
- New features appearing
- Some support for Data products
What do you dislike about the product?
- Not completely clear how to use it with DBT and some other tools.
- API docs HTML page causes browser to freeze because they're too long
- API docs HTML page causes browser to freeze because they're too long
What problems is the product solving and how is that benefiting you?
Giving me end-to-end observability in BigQuery including simple lineage and column level lineage
A very effective data observability product with good customer support
What do you like best about the product?
One of the best upsides of Monte Carlo for me is that it catches data incidents you didn't think to check for with explicit tests in your pipeline, tightening feedback loops and enabling you to reduce your time to recovery.
The lineage feature is also very useful to us, and the fact that everything can be done via APIs makes it very engineer-friendly.
The lineage feature is also very useful to us, and the fact that everything can be done via APIs makes it very engineer-friendly.
What do you dislike about the product?
The integration with git for Looker dashboard lineage has been the most painful part for us, as we have many LookML github repos with distributed ownership, so tracking down the admins of those and getting them to set up deploy keys has been a laborious process.
What problems is the product solving and how is that benefiting you?
It provides monitoring coverage for unknown-unknown situations, and we hope that this combined with the incident handling capability will help use reduce time to recovery for data incidents.
The lineage information it gathers isn't just limited to particular pipelines or one database, the fact that it can also incorporate Looker dashboards makes it very convenient for us and helps us to understand and surface the data supply chain behind reports, etc.
The lineage information it gathers isn't just limited to particular pipelines or one database, the fact that it can also incorporate Looker dashboards makes it very convenient for us and helps us to understand and surface the data supply chain behind reports, etc.
Comprehensive solution for ensuring data reliability, freshness and accuracy
What do you like best about the product?
The most helpful about Monte Carlo is the automated monitoring functionality detecting real-time on freshness issues, volume anomaly and alert users promptly. Customer support is top notch as well.
What do you dislike about the product?
Not really any downsides on the provided functionality.
What problems is the product solving and how is that benefiting you?
It ensures data reliability in our data pipelines and reduce data downtime caused by issues such as pipeline failures or infrastructure problems.
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