Reviews from AWS Marketplace
0 AWS reviews
-
5 star0
-
4 star0
-
3 star0
-
2 star0
-
1 star0
External reviews
External reviews are not included in the AWS star rating for the product.
MC is a great tool which comfortably integrates with other tools we use
What do you like best about the product?
Integration with other tools we use
Customization abilities
Customer support via dedicated Slack channel
Customization abilities
Customer support via dedicated Slack channel
What do you dislike about the product?
Limit on query run time
Limit of the amount of queries I can run simultaneously
500 rows limit in the alerting output
Limit of the amount of queries I can run simultaneously
500 rows limit in the alerting output
What problems is the product solving and how is that benefiting you?
Automating pre-planned SQL queries to identify data discrepancies
MC benefits by running the queries on timed sessions, and with customization
MC benefits by running the queries on timed sessions, and with customization
- Leave a Comment |
- Mark review as helpful
MC user review
What do you like best about the product?
It feels solid, well thought-through and reliable. The UI looks confortable and organized. The slack integration and notifications are great. We rely on it now every day to know the health of our data. Every new issue we detect makes use create new rules.
What do you dislike about the product?
Only a very small thing. I found some wording a bit confusing when implementing a new rule. but took me 1 more minute to understand and do what I wanted.
What problems is the product solving and how is that benefiting you?
MC makes us more consiscient of othe quality of our data and processes, so we know we have something checking what's happening all the time - we don't have to do it ourselves. knowing the change in amouts of data movement or changes in the schemas or objects is very helpful.
Great coverage with minimal effort
What do you like best about the product?
As a user who is also responsible for admininstering access and getting other users set up in Monte Carlo, my review covers both sides.
Firstly, Monte Carlo makes it super simple for teams to get their data ingested which therefore reduces the time I need to spend walking them through the process.
Once teams have completed their side of the set up, it only takes me 15 mins to create and set up a brand new team with the out-of-the-box monitors and set up alerting to their chosen Slack channel.
Teams then often use the provided Monte Carlo documentation to go further, setting up custom monitors and sharing their experiences in our internal community channel.
I've since had lots of positive stories from users describing how Monte Carlo caught issues immediately that would have previously festered for a good few days before being spotted.
As a user, the flexibility with setting up new monitors is fantastic and it's easy to do. With some continued improvement we now only have useful alerts coming through to our channel which we can idenify and action straight away.
The support Monte Carlo provide is great and really helps to make sure you're successful.
Firstly, Monte Carlo makes it super simple for teams to get their data ingested which therefore reduces the time I need to spend walking them through the process.
Once teams have completed their side of the set up, it only takes me 15 mins to create and set up a brand new team with the out-of-the-box monitors and set up alerting to their chosen Slack channel.
Teams then often use the provided Monte Carlo documentation to go further, setting up custom monitors and sharing their experiences in our internal community channel.
I've since had lots of positive stories from users describing how Monte Carlo caught issues immediately that would have previously festered for a good few days before being spotted.
As a user, the flexibility with setting up new monitors is fantastic and it's easy to do. With some continued improvement we now only have useful alerts coming through to our channel which we can idenify and action straight away.
The support Monte Carlo provide is great and really helps to make sure you're successful.
What do you dislike about the product?
The UI can often feel dated and a little clunky. You need to know where to go and how to complete steps otherwise you may miss something important during set up. It would be beter if things were more intuitive.
What problems is the product solving and how is that benefiting you?
With so many teams with different skillsets and varying levels of experience creating monitors to observe their data, the out-of-the-box ML monitors make it so simple to get started. This means that teams can very quickly cover their most important datasets without having to spend too much time setting up each. This usually leads to exploring more granular custom monitors.
Having the integration with Slack enables teams to work with Monte Carlo in a core interface for the business making it much more likely that teams interact with their alerts.
Having the integration with Slack enables teams to work with Monte Carlo in a core interface for the business making it much more likely that teams interact with their alerts.
The tool offers automated data monitoring to detect and resolve data quality issues in real-time
What do you like best about the product?
The tool provides early detection of data quality issues & data lineage from source to target, giving visibility of dependencies and the impact it will have on downstreams. It also improves data reliability and reduces the time and effort needed for data debugging
What do you dislike about the product?
there are no downsides. It would be better if we can improve on the speed as its bit on a slower side.
What problems is the product solving and how is that benefiting you?
The tool provides early detection of data quality issues & data lineage from source to target, giving visibility of dependencies and the impact it will have on downstreams. We are using it to improve data reliability by taking action before it is raised by comsumer. It also reduces the time and effort needed for debugging.
Exploring the Monte Carlo Tool
What do you like best about the product?
I am using Montecarlo API's to integarte it with my CI/CD pipeline.
Via pipline i able to create monitors in Montecarlo.
Also. i have option to write a monitors in yaml format.
This feature i like the most.
Via pipline i able to create monitors in Montecarlo.
Also. i have option to write a monitors in yaml format.
This feature i like the most.
What do you dislike about the product?
Monte carlo have Avarge UI not so much user friendly.
What problems is the product solving and how is that benefiting you?
Montecarlo detecting any data anomilies and data issue in early stage to ensure data accaurcy and relaibilty.
It helps us in many ways.
It helps us in many ways.
Data Architect using MC to measure Quality of Supply Chain Data Products ( Data Mesh )
What do you like best about the product?
Ease of use, low or no code, however support for more sophisticated tests, anomaly detections, easy set up of alerts / notifications, api allowing integration with Collibra (data catalouge) to publish DPs SLIs (Service Level Integrations), and cherry on top - column level lineage of DB objects. Great customer support as well
What do you dislike about the product?
The price could be lower, support for more DBs, currently it's only set up on Prod DB
What problems is the product solving and how is that benefiting you?
I use MC to measure run DQ tests / monitors , and report the scores to Collibra to inform end users and the healthiness of the products.
Easy to use
What do you like best about the product?
Easy to use and understand. The time it taskes to develop a monitor is low.
What do you dislike about the product?
It might be tricky to implement complex logic while building alerting
What problems is the product solving and how is that benefiting you?
Helping us catch data quality issues
Exceptional Data Quality Monitoring with Monte Carlo
What do you like best about the product?
Monte Carlo has proven to be an essential tool for monitoring data quality, helping us identify incidents before they are detected elsewhere. This has enabled us to promptly alert the appropriate teams as soon as issues arise. The support team has been exceptional—always responsive, patient with our questions, and committed to making continuous improvements. They genuinely value our feedback and take the time to understand our specific use cases. Overall, it's been a great experience working with both the tool and the Monte Carlo team.
What do you dislike about the product?
The results can sometimes be challenging to interpret. However, I am hoping that with time and familiarity, it might become easier to navigate.
What problems is the product solving and how is that benefiting you?
MC is helping us identify data quality issues before they are detected elsewhere. Its ability to integrate with tools like slack, email for notifications has been incredibly powerful as this enabled us to promptly alert the appropriate teams as soon as issues arise, thus saving time and impact on the business
5 Reasons You Shouldn't Get MonteCarlo for your Business
What do you like best about the product?
You Should't Get MonteCarlo If....
1. You like waking up everyday not knowing whats broken in your data pipelines. You always wanted to tackle Data like the Wild West.
2. You'd rather write your own custom ML alerts for ALL your data warehouse rather than having an easy out-of-the-box auto-alerting solution. How else would you prove to your manager you're a 10x Engineer.
3. You believe having a data lineage app is for babies. Real data engineers have the entire lineage map in their heads written in SQL.
4. You don't like tracking data incidents. I get it, sweeping problems under the rug makes the bad feelings go away.
5. You think 3rd party integrations to apps like Slack, Airflow and Cloud Data Warehouses like Snowflake & BigQuery is overrated.
1. You like waking up everyday not knowing whats broken in your data pipelines. You always wanted to tackle Data like the Wild West.
2. You'd rather write your own custom ML alerts for ALL your data warehouse rather than having an easy out-of-the-box auto-alerting solution. How else would you prove to your manager you're a 10x Engineer.
3. You believe having a data lineage app is for babies. Real data engineers have the entire lineage map in their heads written in SQL.
4. You don't like tracking data incidents. I get it, sweeping problems under the rug makes the bad feelings go away.
5. You think 3rd party integrations to apps like Slack, Airflow and Cloud Data Warehouses like Snowflake & BigQuery is overrated.
What do you dislike about the product?
Nothing to say that I dislike. Only a few items on my wishlist to for new features that would really help my org.
1. Integration with GCP Dataform
2. Greater Data Catalog abilities.
3. Custom API integrations to auto run workflows after a trigger.
1. Integration with GCP Dataform
2. Greater Data Catalog abilities.
3. Custom API integrations to auto run workflows after a trigger.
What problems is the product solving and how is that benefiting you?
MonteCarlo's main benfit we felt immediately was it's automated monitoring of the tables & data assets.
Without having to set up a cusom alert for every single table, MonteCarlo automatically trains on a baseline for each table you give it access to.
It figures out expected update frequencies, row number changes, schema changes, field anomalies, etc.
Thanks to this, tables we forget to monitor are automatically tracked and alerted on when there is an issue or change.
We have important production tables that suddenly behave differently, and we are able to quickly track bugs and outages that were realted to the anomaly.
Without having to set up a cusom alert for every single table, MonteCarlo automatically trains on a baseline for each table you give it access to.
It figures out expected update frequencies, row number changes, schema changes, field anomalies, etc.
Thanks to this, tables we forget to monitor are automatically tracked and alerted on when there is an issue or change.
We have important production tables that suddenly behave differently, and we are able to quickly track bugs and outages that were realted to the anomaly.
A Promising Yet Imperfect Tool for Data Observability
What do you like best about the product?
Pros:
Good intentions and potential
Simplifies alert systems and visualization
Good intentions and potential
Simplifies alert systems and visualization
What do you dislike about the product?
Cons:
ML thresholds are not effective for metrics that vary based on time factors
Manual checks/ query implementation are still necessary
Uncertain if it is worth the investment
ML thresholds are not effective for metrics that vary based on time factors
Manual checks/ query implementation are still necessary
Uncertain if it is worth the investment
What problems is the product solving and how is that benefiting you?
Data quality checks
showing 11 - 20