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Jelena Mataija - Vroom
What do you like best about the product?
Overall a really nice tool to monitor data quality and validity.
Setup is quiet easy enough if you prepare in advance properly, where lovely support comes along and they are always ready to help and to review if needed.
Machine learning program can detect if data hasn’t been received on frequent time giving us time to focus on other things and not to monitor our pipelines constantly. As well as slight hints in data quality changes which can come in handy.
Customised queries are a nice touch and implementation is endless.
For daily data ingestions and quality check this is a nice tool to have since it will alert you on time if anything "fishy" is going on giving you time to focus on other things.
If set up correctly there are dashboards that can be shared with different teams throughout the organisation for data monitor and for some internal audits as well.
Setup is quiet easy enough if you prepare in advance properly, where lovely support comes along and they are always ready to help and to review if needed.
Machine learning program can detect if data hasn’t been received on frequent time giving us time to focus on other things and not to monitor our pipelines constantly. As well as slight hints in data quality changes which can come in handy.
Customised queries are a nice touch and implementation is endless.
For daily data ingestions and quality check this is a nice tool to have since it will alert you on time if anything "fishy" is going on giving you time to focus on other things.
If set up correctly there are dashboards that can be shared with different teams throughout the organisation for data monitor and for some internal audits as well.
What do you dislike about the product?
You have to have a dedicated people to maintain the monitors and constant update since it is a mechine learning program, meaning you cannot get lazy with it.
Ocasionally it can overwellm a database resources but than again it depends on your company organization.
Ocasionally it can overwellm a database resources but than again it depends on your company organization.
What problems is the product solving and how is that benefiting you?
For us currently most used scenarios are ones where we get alert if our data volumes have been changed. If we do not expect it than this is a good signal that our pipelines are late or broke, often those that are coming from third party or API's.
Also several custom monitors are in place to track duplicates in our data, fluctuations in group volumes etc.
The ones where we check for unique values are really helpful, they can give us a heads up if we need to implement some other changes in our transformation models.
Also several custom monitors are in place to track duplicates in our data, fluctuations in group volumes etc.
The ones where we check for unique values are really helpful, they can give us a heads up if we need to implement some other changes in our transformation models.
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MC helps us deliver better results more efficiently.
What do you like best about the product?
It is a great tool for getting a general high level overview of the state of our data sources and pipelines.
Automated default monitors (like volume and source freshness anomaly detectors) are also working well and a great resource for us!
Automated default monitors (like volume and source freshness anomaly detectors) are also working well and a great resource for us!
What do you dislike about the product?
Field lineage could be improved, although that's a hard problem to solve.
Tiny UI issues/small bugs from time to time.
More visibility to their platform vision & how to leverage more and better Monte Carlo to its full extent
Tiny UI issues/small bugs from time to time.
More visibility to their platform vision & how to leverage more and better Monte Carlo to its full extent
What problems is the product solving and how is that benefiting you?
Source freshness and volume anomaly alerting; Monitoring different sets of data and alerting us on custom-defined anomalies;
Great post production data quality tool.
What do you like best about the product?
Full confidence about my data quality. After applying monitors on top of my datasets, I can rest assure that the data is correct and accessible.
Moreover, our customer support is good when needde.
Moreover, our customer support is good when needde.
What do you dislike about the product?
Slack notifications payload design - In case I want to create a custom monitor and send an "advanced" and more informative payload, it's not that easy and accessible.
What problems is the product solving and how is that benefiting you?
Data freshness - be aware of latency so we'll be able to notify our data consumers. Data anomalies, Schema changes, nulls ext. - Monte helps us be in control over our hundreds of data assets, so we can focus on the most needed tasks and bugs.
Moreover - The slack integration with the user-set statuses helps us understand which incidents is being taken care of already, and which still requires our attention.
Moreover - The slack integration with the user-set statuses helps us understand which incidents is being taken care of already, and which still requires our attention.
End-to-end easy visibility of the data
What do you like best about the product?
Monte Carlo helps us to identify any potential inconsistency in the data framework at a quick glance. It helps flag cases that would be difficult to identify otherwise
What do you dislike about the product?
No major things, though after using other software to alert on inconsistencies with the business, I think that would be usefult that MC allows notification to contain tables with the hits that have created the alert.
It is useful for the business to easily check the alert driver and some columns that may be useful for them
It is useful for the business to easily check the alert driver and some columns that may be useful for them
What problems is the product solving and how is that benefiting you?
Analyse big pipelines end to end
Monte Carlo helps us in Data Observability
What do you like best about the product?
We get alerts from Monte Carlo as per schema change, null pct change, etc, which gives us insights of data changes of important tables.
What do you dislike about the product?
Sometimes we receive alerts of tables not in our domain.
What problems is the product solving and how is that benefiting you?
Monte Carlo helps monitor changes of each specified attribute, which is almost impossible to do manually.
Monte Carlo let me control the chaos I have in my database
What do you like best about the product?
The frequency of the new super-useful features release and the ease of use over other DQ tools.
What do you dislike about the product?
I'm looking forward for better incidents management, especially filtering, grouppping and navigation.
What problems is the product solving and how is that benefiting you?
With monte carlo we can provide a quicker response on the data quality issues to our end users. Previously data quality checks were either not implemented (hence we had to check our data manually) or were distributed in a various sets of custom scripts that were not easy to run, maintain and understand.
Automated and evolving insights on your Data Mesh - Data Products
What do you like best about the product?
They are innovative and every month, I'm getting a new feature on my dashboard. The intergation with other Data Engineering tools is great. Monitoring as a Code or UI based monitoring management is very easy. The team is very responsive in term of customer support either for new feature or bug fixes.
What do you dislike about the product?
The naming conventions are a bit un orthodox or confusing at times.
I'm waiting for more evolved dashboarding features.
I'm waiting for more evolved dashboarding features.
What problems is the product solving and how is that benefiting you?
I'm able to monitor data availablity and qulaity matrics very easily. Do get alerts and automated management on the same.
- It's help me generate/capture SLIs on My Data Products and share them with stakeholders and potential consumers of my data.
- It's help me generate/capture SLIs on My Data Products and share them with stakeholders and potential consumers of my data.
Monte Carlo is a Game Changer
What do you like best about the product?
Monte Carlo is a tool that is easy to implement, use, and drive value through for users across our organization. In our case, we started seeing value during the first week of our proof of concept (POC) period and have continued to generate more value since!
A big reason for this is that Monte Carlo not only helps identify a data anomaly faster than we had ben able to before, but also quickly enables users to understand the context and impact of the event. Lineage, Impact Analysis, Correlation Analysis, and integrations with various tools helps you put the alert into context and also resolve the issue much faster than an out of context alert.
Outside of the abilities of the core product, the support team is top notch and actively takes feedback to enhance the product. The team is truly customer first. We have never had a customer support request fall off the radar and they are always proactive in making sure we find the best solution for our needs.
Lastly, Monte Carlo is a tool designed for scale and the product is centered around making it easy for an organization to standup up a data quality program (with support activities) all through the tool.
A big reason for this is that Monte Carlo not only helps identify a data anomaly faster than we had ben able to before, but also quickly enables users to understand the context and impact of the event. Lineage, Impact Analysis, Correlation Analysis, and integrations with various tools helps you put the alert into context and also resolve the issue much faster than an out of context alert.
Outside of the abilities of the core product, the support team is top notch and actively takes feedback to enhance the product. The team is truly customer first. We have never had a customer support request fall off the radar and they are always proactive in making sure we find the best solution for our needs.
Lastly, Monte Carlo is a tool designed for scale and the product is centered around making it easy for an organization to standup up a data quality program (with support activities) all through the tool.
What do you dislike about the product?
I think there are still some enhancements actively being made to help users more easily administer the tool, but overall, there are not any big dislikes about Monte Carlo.
What problems is the product solving and how is that benefiting you?
Monte Carlo has given us end to end observaiblity of key data pipelines that power the core of our business. Data trust is a key factor in any analysis and Monte Carlo has increasingly enabled us to trust our data and quickly take action when things begin to look off.
Montecarlo review
What do you like best about the product?
- easy to integrate with current ecosystem ( data warehouse, dasboarding tool, SQL applications)
-UI are modern and userfriendly
-ML capabilties can identify a good porton of data issues
-UI are modern and userfriendly
-ML capabilties can identify a good porton of data issues
What do you dislike about the product?
we had some points in the past months but the team is addressing them rapidly
What problems is the product solving and how is that benefiting you?
-Issues on data pipeline
-Proactive data monitoring
-Proactive data monitoring
The ultimate guard for data issues
What do you like best about the product?
Good response time from their support team.
The support team really tries to understand our use cases.
Automatic monitors have been super useful for data engineering purposes.
Custom SQL rules look promising for anomaly detection.
dbt integration has been very useful for the analytics engineering team.
We appreciate the possibility to test beta features, like the Performance tab, which has been very helpful to us in a couple of projects.
We use it daily to review incidents and document.
The support team really tries to understand our use cases.
Automatic monitors have been super useful for data engineering purposes.
Custom SQL rules look promising for anomaly detection.
dbt integration has been very useful for the analytics engineering team.
We appreciate the possibility to test beta features, like the Performance tab, which has been very helpful to us in a couple of projects.
We use it daily to review incidents and document.
What do you dislike about the product?
Our BI tool, Metabase, is currently not supported.
What problems is the product solving and how is that benefiting you?
- Monitoring of data engineering pipelines. Monte Carlo has proven that logging tools such as Datadog are not enough for data engineers.
- Performance monitoring for analytics engineering.
- Performance monitoring for analytics engineering.
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