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Game changer for the observability of a data platform
What do you like best about the product?
The out-of-the-box monitors based on ML.
What do you dislike about the product?
Still room of improvement in terms of UI and time to reflect in the interface changes applied to the configuration of assets and monitors.
What problems is the product solving and how is that benefiting you?
Applying data monitors at scale
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Monte Carlo: an experience end-to-end for monitoring data quality
What do you like best about the product?
As a tool:
- it is straightforward to set up / implement with the out-of-the-box connectors
- great out-of-the-box monitors / visualization
- great incident management features
- the UI is very user-friendly
And a great customer support team!!
- it is straightforward to set up / implement with the out-of-the-box connectors
- great out-of-the-box monitors / visualization
- great incident management features
- the UI is very user-friendly
And a great customer support team!!
What do you dislike about the product?
- Cannot detect an incident before a code is pushing into production: only when it's running in production
- We tried to implement a connection between a SQL Server and Monte Carlo and the connection between Monte Carlo and this on-premise instance wasn't the easiest to manage by knowing that the features proposed by this connector are quite limited
- We tried to implement a connection between a SQL Server and Monte Carlo and the connection between Monte Carlo and this on-premise instance wasn't the easiest to manage by knowing that the features proposed by this connector are quite limited
What problems is the product solving and how is that benefiting you?
To detect incidents in real-time and to be pro-active in the incidents solving
We use MC to monitor a significant number of our tables.
What do you like best about the product?
Good connectivity between different tools e.g. slack, links go directly to GCP BQ etc
What do you dislike about the product?
We have many slack updates set up and the slack updates provide significantly less detail than the images produced on the MC incident page itself
What problems is the product solving and how is that benefiting you?
Allowing us to let our processes run automatically without having to frequently check our tables for data quality. Issues in our source data or processes are identified and the alert is sounded before these issues can reach the business
Monte Carlo Integration for GCP DWH
What do you like best about the product?
Monte Carlo helps us keep a close eye on our data warehouse. Examples include notifying us of major changes in volume or freshness, which helps us get ahead of potential issues, and table / column lineage, which lets us see the impact of any changes to dependent tables / reports. I'm sure there are other useful features which we haven't explored yet too.
What do you dislike about the product?
No major downsides. Would like more customisation on notifications as they can be quite verbose. Maybe a few more options around the Inisght reports would be useful too. And maybe a dark mode for the GUI...... (it's on my wishlist for GCP itself as well.....).
What problems is the product solving and how is that benefiting you?
Daily DWH changes and issues.
Impact assessment.
Old / unused fields and tables.
Impact assessment.
Old / unused fields and tables.
Easy to use, helps bring insight into areas we had no awareness.
What do you like best about the product?
Implementation was pretty simple and straightforward. Support helped upgrade our collector and respond to our questions quickly. The UI has been updated with many features over time, and we are recently enjoying the performance tab for long-running write and read queries.
I comb through the alerts and monitors weekly to understand the patterns and use cases better. We have an on-call rotation that leans into incidents generated by Monte Carlo.
I comb through the alerts and monitors weekly to understand the patterns and use cases better. We have an on-call rotation that leans into incidents generated by Monte Carlo.
What do you dislike about the product?
The feedback loop for our dbt runs are not immediate. If we have an issue with a model that causes skips we don't have an easy way to understand this and action on it in Monte Carlo which stops us from leaning deeper into the incidents workflow.
The insights in the performance tab are great, but it's not easy to drill down and you can't export.
I'd love to see top level if one table has an issue here are every downstream reports impacted as a snapshot of sharing to users.
The insights in the performance tab are great, but it's not easy to drill down and you can't export.
I'd love to see top level if one table has an issue here are every downstream reports impacted as a snapshot of sharing to users.
What problems is the product solving and how is that benefiting you?
Montecarlo has been very helpful for identifying issues with the breadth of jobs we have running. If something isn't updating as expected or a change happens and volumes spike, it's helped us resolve incidents immediately that may have otherwise been unseen.
We have also been building out domain-specific reporting to understand better which areas need improvement
We have also been building out domain-specific reporting to understand better which areas need improvement
Use of Monte Carlo Data Quality and Observability in Data Management
What do you like best about the product?
Ease of use and breadth of market leading capabilties, such as data lineage checks. Strong customer support and features request process.
What do you dislike about the product?
There is nothing that comes immediately to mind.
What problems is the product solving and how is that benefiting you?
The Observability checks ensure that the data freshness and volume checks are ensuring the right data is availble at the right time. This is important to the busienss users of the data.
Great out-of-the-box solutions and easy to deploy using infrastructure as code
What do you like best about the product?
- Really easy to set up the out-of-the-box monitors
- Generally quick cutomer service and response times
- Easy to monitor multiple tables in one place
- API explorer enabled us to explore the API before making use of the SDK
- Integration with Opsgenie and Slack
- Generally quick cutomer service and response times
- Easy to monitor multiple tables in one place
- API explorer enabled us to explore the API before making use of the SDK
- Integration with Opsgenie and Slack
What do you dislike about the product?
- Using the SDK was a bit challenging and the documentation could be improved
- Setting up custom monitors was a bit hit and miss
- Would like there to be better integration with Google Cloud services
- Setting up custom monitors was a bit hit and miss
- Would like there to be better integration with Google Cloud services
What problems is the product solving and how is that benefiting you?
Using Monte Carlo to monitor tables freshness means that we don't have to create monitors ourselves.
Exploring using Monte Carlo for trying to monitor SLOs, would like a way to integrate this with Google Cloud Monitoring.
Exploring using Monte Carlo for trying to monitor SLOs, would like a way to integrate this with Google Cloud Monitoring.
Seamless and invaluable level of insight observability to focus on enrichment and innovation.
What do you like best about the product?
Being part of the Data Team, MC is getting us timely intel on both edge case issues and more common BAU ones that crop up from time to time.
MC alerting identifies what it believes to be out of the ordinary coupled with it's in-built lineage tool reducing our time spent on investigation and quicker resolutions.
A direct consequence of this being the number of data related queries from data consumers in our business has significantly dropped.
MC alerting identifies what it believes to be out of the ordinary coupled with it's in-built lineage tool reducing our time spent on investigation and quicker resolutions.
A direct consequence of this being the number of data related queries from data consumers in our business has significantly dropped.
What do you dislike about the product?
There are no dislikes from me on the MC product as a whole and it is evolving so looking forward to whats to come. There is a lot of information available and thats certainly not a bad thing, one tiny nit would be a way to group issues from multiple pipeline streams which are related.
What problems is the product solving and how is that benefiting you?
Timely intel for key Data Warehouse tables e.g
- Unusually stale tables which can be from 3rd party syncing functions issues
- Alerting on duplicate keys in reporting tables
- Table schema changes
With this sort of visibility we have better control over our data which depends on many different pipelines, consolidating all that reporting and alerting is invaluable.
- Unusually stale tables which can be from 3rd party syncing functions issues
- Alerting on duplicate keys in reporting tables
- Table schema changes
With this sort of visibility we have better control over our data which depends on many different pipelines, consolidating all that reporting and alerting is invaluable.
Easy to use!
What do you like best about the product?
The monitors as code YAML configuration is great for managing our monitors, and creating reusable configurations. Customer support have also been great with any issues or questions we've had.
What do you dislike about the product?
More integrations with our existing observability tools such as DataDog and Grafana would be great.
What problems is the product solving and how is that benefiting you?
We have a lot of data created by many different teams and Monte Carlo is helping us build confidence and trust in our datasets so that we can use them for critical functions as well as for other teams to use for analysis.
Useful insights about our data straight out of the box
What do you like best about the product?
It's very easy to connect and set up some monitors off the shelf which provide very helpful observations about our data. These have already helped us identify and address some issues with very little effort on our part.
What do you dislike about the product?
At times it's obvious that Monte Carlo is still quite a young product. For example the audiences/notifications section is a little clunky, it's sometimes hard to replicate functionality that's in the web console in the CLI, and we had some issues where monitors failed to run because of a configuration error but they weren't notifying us of the failure. However the team at monte carlo have been very receptive to feedback and quickly made product improvements in response.
What problems is the product solving and how is that benefiting you?
Identifying issues in our data
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