Monte Carlo Data + AI Observability Platform
Monte Carlo DataReviews from AWS customer
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Good, convenient, fast product
What do you like best about the product?
Convenient flexible setup of monitors and alerts; custom SQL covers almost all needs. The Table Lineage section is very convenient and useful. Good support.
What do you dislike about the product?
Lack of timestamp parameterization for monitor launches.
Not very convenient display of Tableau workbooks in the Lineage and Assets - Report sections.
And it would be convenient to have the ability to import descriptions for table and fields from Redshift data warehouse
Not very convenient display of Tableau workbooks in the Lineage and Assets - Report sections.
And it would be convenient to have the ability to import descriptions for table and fields from Redshift data warehouse
What problems is the product solving and how is that benefiting you?
Fast and convenient setup of automatic monitoring and user notification
Broad feature set, does what it says on the tin
What do you like best about the product?
Reduces pipeline complexity to actionable insights. Broad set of integrations. Love the API.
What do you dislike about the product?
Keep working on the UI/UX - UI could be more sleek.
What problems is the product solving and how is that benefiting you?
Detecting and reporting silent failures in a timely manner
Anomaly detection you would never detect without Monte Carlo
What do you like best about the product?
The few configuration necessary to get started. Monte Carlo really is a smart tool working on his own, and I find this great.
What do you dislike about the product?
The lack of Monitor as Code capabilities. OPS Analytics aims to have all conf stored as code (Terraform)
The lack of the possibility to control monitored/observable assets easily.
The lack of the possibility to control monitored/observable assets easily.
What problems is the product solving and how is that benefiting you?
Detect anomalies before end-users find about them in their dashboard.
Save time on resolution using insights.
Save time on resolution using insights.
Useful monitoring tool
What do you like best about the product?
Slack updates and alerts on data model changes, possible errors, delayed updates, etc. It's a convenient way, espescially for data consumers, to keep an eye on the health of the pipeline and the freshness of the data they are using.
What do you dislike about the product?
There is the usual problem of alert fatigue, but that's not surprising. What is more difficult is that when a model does not update, or when a test fails, that the actual source is harder to pinpoint. There is not a clear way to see what caused an error, or why.
There have also been issues where resolutions of errors are not reported.
There have also been issues where resolutions of errors are not reported.
What problems is the product solving and how is that benefiting you?
Most usefully it is wide scale alerts when there are database issues. Recent developments like linking alerts to git PRs is also a good step in the right direction, although it could be smarter. For example, if a model fails downstream because of a PR change that isn't always picked up as related.
Good product experience with help in data observability and job monitoring
What do you like best about the product?
Notifications -- Slack channels help and GUI is user friendly
What do you dislike about the product?
Data lineage support - Per our architectire we need to look through columns usage in various reports and tables. Having data lineage support would be very helpful.
What problems is the product solving and how is that benefiting you?
Data gaps, when a regular job didnt load the data per schedule.
Schema changes - New data columns started flowing
Data Anamolies
Schema changes - New data columns started flowing
Data Anamolies
Easy monitoring
What do you like best about the product?
The builtin monitors have a good coverage, and the database is quite good monitored with not much effort. Also the custom monitors are easy to implement.
What do you dislike about the product?
It is being quite painful to create alerts and domains containing a large number of tables, especially from different databases. That said, once everything is created works fine.
I miss an api to just changing something or adding tables to a domain, Update instead or CreateorUpdate, without the need of adding all the assests each time.
I miss an api to just changing something or adding tables to a domain, Update instead or CreateorUpdate, without the need of adding all the assests each time.
What problems is the product solving and how is that benefiting you?
Mainly the freshness of the Analytics sources, as we are not the owners and had not visibility until the data reached to Analytics
data engineer
What do you like best about the product?
the fact that 100% of my tables are monitored, that all thresholds can be dynamically configured by the ML, and the UI is super easy to use it makes debugging easy
What do you dislike about the product?
- no slack owner assignments
- queries that are sent to Snowflake are not optimized
- no monitoring on read query performance
0 lineage is too much, and hard to navigate and filter out assets, and when I filtered out assets, except that nothing would be there, and the screen would adjust
- queries that are sent to Snowflake are not optimized
- no monitoring on read query performance
0 lineage is too much, and hard to navigate and filter out assets, and when I filtered out assets, except that nothing would be there, and the screen would adjust
What problems is the product solving and how is that benefiting you?
monitoring all data
Monte Carlo provide reliable and accurate data observability to our data stack.
What do you like best about the product?
I like the most about Monte Carlo is the Automated Monitoring functionality. Because it remove the hassles of need to create monitor for each tables, by automatically applied the Freshness, Volume and Schema change monitor to any new table imported to our database.
What do you dislike about the product?
Most dislike is its UI. I feel that the UI is not inituitive. Eg;
What problems is the product solving and how is that benefiting you?
Monte Carlo help to automates thousand of tables in our databases. It provide a consistent observability and come with multiple monitoring option. Plus we can integrate Monte Carlo to our Slack channel to provide alert to our team. With Monte Carlo, we dont need manually create a custom SQL script for our tables, as Monte Carlo helps to automate those task
Very easy to onboard with an excellent team that tailors their work to our success
What do you like best about the product?
Monte Carlo is very easy to use and connecting it to our stack was fairly simple. The documentation on their university allowed us to operate at scale, we only needed core employees to have access to live sessions and they quickly got up to speed to train others.
The fact that we can get immediate support using slack, email or any other channel, with instant feedback, gave us that extra reassurance that we were going to be well cared.
On top of that, Monte Carlo has a lot of monitoring features that make our life easier and point us in the right direction in the journey of improving our data observability experience.
The fact that we can get immediate support using slack, email or any other channel, with instant feedback, gave us that extra reassurance that we were going to be well cared.
On top of that, Monte Carlo has a lot of monitoring features that make our life easier and point us in the right direction in the journey of improving our data observability experience.
What do you dislike about the product?
The fact that we can create monitors "as code" / via API is awesome, but they are not compatible with the visual configuration interface, meaning that we are not able to automate the release of new tables with automatic monitors and, at the same time, allow less technical people to tune the monitors from an easier interface. This is not a deal breaker and is definitely in their long term roadmap, but not release yet
What problems is the product solving and how is that benefiting you?
Decrease SLA for MTRR (time to detect and fix) for data problems in production
Improve the data trustworthiness with data product owners
Scale the number of data products without increasing the number of people to upkeep them
Improve the data trustworthiness with data product owners
Scale the number of data products without increasing the number of people to upkeep them
Great onboarding processes, fast communication, continues development - new features each month
What do you like best about the product?
Monte Carlo enabled us to quickly integrate data quality into our data pipelines. Their onboarding process was briliant and helped us alot in understanding of data quality issues. Additionaly their platform is very mature in features and while providing great UI it also provides API's that can be used to incorporate those features programmatically.
What do you dislike about the product?
Lack of terraform provider to enable Infrastructure as a Code integration.
API limits are very low but can extended by contacting customer support.
Missing clean and concise tracking of raised issues and requested features.
API limits are very low but can extended by contacting customer support.
Missing clean and concise tracking of raised issues and requested features.
What problems is the product solving and how is that benefiting you?
Data quality in data pipelines. Data lineage. Notification framework enabling fast and reliable information directly to the data producers/consumers/stakeholders.
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