Monte Carlo Data Observability Platform
Monte Carlo DataReviews from AWS customer
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Monte Carlo
What do you like best about the product?
It helps us detect data quality issues in our systems much sooner than we 'd be able to without it. The UI is mostly intuitive / easy to navigate.
What do you dislike about the product?
The machine learning thresholds can still be a little be unreliable (we still get alerts about things we don't actually need to respond to).
What problems is the product solving and how is that benefiting you?
It helps us recognize if we have irregular data and enables us to fix the underlying issue faster.
Experience with monte carlo is very good. We are able to proactively look into any issues and solve.
What do you like best about the product?
Monte carli is best to proactively work on incidents and solve them before business raise any concern.
What do you dislike about the product?
Sometimes freshness anomolies and volume anomalies are merged under one category.
What problems is the product solving and how is that benefiting you?
Due to monte carlo we are able to practively look into any incident before business raise any concern and solve it to maintain data integrity.
All your monitoring in one place
What do you like best about the product?
The ability to leverage both custom and automated monitoring and integrate with tools like Slack
What do you dislike about the product?
Missing grouping features - would be really useful to be able to group (or search) for related alerts in order to easily clear once the underlying issue has been resolved
What problems is the product solving and how is that benefiting you?
Alerting on failed database ETLs in order to ensure our data latency remains low
It helps me to check that tables are well landed like no other tool
What do you like best about the product?
The notification system is great, and also the integration with other systems such as PowerBI or Snowflake. It helps our company to ensure that tables are well landed, making Data Engineering processes more agile.
What do you dislike about the product?
Probably the Customer support could improve the engagement with our company, helping to get the most out of the tool.
What problems is the product solving and how is that benefiting you?
It allows me to ensure that the tables are well landed into the data warehouse
Good observability tool with some flaws
What do you like best about the product?
It is easy to understand for a Technical user. It has a variety of features that enhance Data Engineering work.
What do you dislike about the product?
The interface cannot be modified depending on user roles. The explanations that Monte Carlo provides are very technical, and business users usually struggle with them.
What problems is the product solving and how is that benefiting you?
It helps me to see how often tables are refreshed.
Monte carlo Review
What do you like best about the product?
1.It identify any data issues quickly,
2.tracks data across pipeline
3.real time monitoring.
4.can connect to all tools
2.tracks data across pipeline
3.real time monitoring.
4.can connect to all tools
What do you dislike about the product?
1. slow interface
2. it has complex steup
2. it has complex steup
What problems is the product solving and how is that benefiting you?
1. Schema changes detaction which can scuse metadata curroption.
2. checking freshness of data wheather data is loading on time.
3. checking volume of data.
2. checking freshness of data wheather data is loading on time.
3. checking volume of data.
The tool that continuously monitors data, identify and resolving the quality issues in real-time
What do you like best about the product?
The tool helps in detecting data quality issues early and tracks data flow from source to target. It offering clear insights into dependencies and their impact on downstream systems. By enhancing data reliability, it also cuts down the time and effort required for troubleshooting.
What do you dislike about the product?
There aren't any major drawbacks, but the speed could use some improvement as it tends to be a bit slow. Also, the old UI was quite good.
What problems is the product solving and how is that benefiting you?
Monte carlo detecting the freshness,volume and schema changes of the tables. It helps us to detect and resolve the issue before the client came to us.
Mainly a great tool for observability but too technical
What do you like best about the product?
It is integrated with our main systems in the company and it also provides an intuitive interface. On a daily bases, it helps me to detect issues on the tables and views that, otherwise, I would not detect.
What do you dislike about the product?
Implementing Montecarlo has a learning curve, and it is not easy to adopt it by non-technical people. It would be good that in next versions Monte Carlo focuses on providing a site to learn more about the tool.
What problems is the product solving and how is that benefiting you?
Mainly issues in the load of tables.
Helping ease process and communication
What do you like best about the product?
Monte Carlo was very helpful in aligning and working with stakeholders to help show what kinds of issues a Data Platform team could monitor effectively, and where we would need more business involvement.
While it can be easy for engineers to scoff at queries to the information schema, the overall tool was very helpful in providing an archive of experiences and helped us build runbooks around actions taken by both senior and junior engineers.
While it can be easy for engineers to scoff at queries to the information schema, the overall tool was very helpful in providing an archive of experiences and helped us build runbooks around actions taken by both senior and junior engineers.
What do you dislike about the product?
The in built query editor and AI autocomplete tools can be a bit frustrating to work with - our folks will typically just copy from native sql tools.
I can't say this is a dislike, but rather an outcome that could have gone wrong.
The ease of set up can quickly create a deluge of new alerts - especially out of the box anomaly detection - where not everyone understands what is running or how to respond, or if stakeholders need to worry. We were fortunate to have an appropriate amount of time running in production with the teams that will use it, before bringing our few stakeholders together, and were able to determine (rather ad hoc) what was meaningful and what wasn't.
I can't say this is a dislike, but rather an outcome that could have gone wrong.
The ease of set up can quickly create a deluge of new alerts - especially out of the box anomaly detection - where not everyone understands what is running or how to respond, or if stakeholders need to worry. We were fortunate to have an appropriate amount of time running in production with the teams that will use it, before bringing our few stakeholders together, and were able to determine (rather ad hoc) what was meaningful and what wasn't.
What problems is the product solving and how is that benefiting you?
Run book creation, archive of past experiences with runbooks, alignment towards data quality types, communication within our team and with other teams around us.
Monte Carlo has been a great tool to connect data & engineering functions in a simple UI.
What do you like best about the product?
1. Very simple minimum requirements for alerts (threshold + short sql query)
2. Email / slack alerts is very neat & easy
3. Ability to search alerts by alert name & last modifided name
2. Email / slack alerts is very neat & easy
3. Ability to search alerts by alert name & last modifided name
What do you dislike about the product?
1. Not being able to search alerts by creator's name
2. Cluttered Alert UI - Notifications & Details in Alert Details section
3. Difficulty grouping alerts
4. Consistent problems with algorithimic thresholds becoming far too insensitive (including 0), and had to switch to manual thresholds.
2. Cluttered Alert UI - Notifications & Details in Alert Details section
3. Difficulty grouping alerts
4. Consistent problems with algorithimic thresholds becoming far too insensitive (including 0), and had to switch to manual thresholds.
What problems is the product solving and how is that benefiting you?
The data-product connection within my organiztion is very robust through dashboarding, reports, etc... However, there is far fewer pathways to connect the data function to engineers and make data available. Through Monte Carlo we have a simple way to allow engineers to view feature preformance (and more importantly outages), to begin approaching fixes even if an analyst isn't directly involved.
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