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great tool and service
What do you like best about the product?
how the ML evolve as more information is provided.
the lineage
the lineage
What do you dislike about the product?
sometime it can be a little noisy.
there is an opportunity for this to be used as a catalog but it is not as user friendly for that.
no s3 check
there is an opportunity for this to be used as a catalog but it is not as user friendly for that.
no s3 check
What problems is the product solving and how is that benefiting you?
giving headsup if incorrect or incomplete data
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Great tool to monitor the data quality!
What do you like best about the product?
Monte Carlo is very easy to onboard and user-friendly. Setting up data quality monitors is straightforward, allowing us to detect problems right away in case of any breaches. Alerts can be sent to respective Slack channels, making the appropriate people aware. Since adopting Monte Carlo, the data quality governance capabilities in our company have increased tremendously!
What do you dislike about the product?
There are many types of monitors, which can be confusing at times regarding the conditions under which to use them.
What problems is the product solving and how is that benefiting you?
As a rapidly growing company, we generate a vast amount of data and require timely monitoring to swiftly detect and inform the right people to address any issues. Monte Carlo enables us to set up all the monitors in one place and view data quality problems at a high level. Any specific breaches are sent to a Slack channel and resolved by the respective individuals.
Data Observability Platform that Delivers
What do you like best about the product?
Getting value with minimal cusom work
Ease of Integration and implementation
Customer support team are great and always assisting and answering our inquiries
Ease of Integration and implementation
Customer support team are great and always assisting and answering our inquiries
What do you dislike about the product?
Need a bit more controls over the ML model sensitivity to reduce manual work of creating custom freshness/volume monitors
Would appriciate a bit more ease of use on the platform management capabilties (e.g. managing dataset and table monitoring)
Would appriciate a bit more ease of use on the platform management capabilties (e.g. managing dataset and table monitoring)
What problems is the product solving and how is that benefiting you?
Moving our data engineering team to be much more proactive when it comes to finding and fixing data and data pipelines related issues
Get back the trust of your stakeholders!
What do you like best about the product?
As a data analyst, one of the standout features that I absolutely love is its ability to proactively detect and alert on data issues, and fix them before the stakeholders send you on Slack "something seems off with the numbers".
Moreover, the platform's intuitive interface deserves a special mention. It simplifies complex data lineage, making it easy to trace the journey of every piece data model. The visualizations provide a clear picture of dependencies, helping to understand the impact of any changes.
The Customer Support/onboarding team are very reactive and are always here to help. Always available to help or even to configure any alerts with you based on your use-cases. The integration of the tool also went quite smoothly as the onboarding was very complete and structured from A to Z.
Moreover, the platform's intuitive interface deserves a special mention. It simplifies complex data lineage, making it easy to trace the journey of every piece data model. The visualizations provide a clear picture of dependencies, helping to understand the impact of any changes.
The Customer Support/onboarding team are very reactive and are always here to help. Always available to help or even to configure any alerts with you based on your use-cases. The integration of the tool also went quite smoothly as the onboarding was very complete and structured from A to Z.
What do you dislike about the product?
Honestly, not much. The learning curve for new users might be a bit steep, especially for those not familiar with data observability problems. I would say that the benefits far outweigh any minor drawbacks.
What problems is the product solving and how is that benefiting you?
The tool helps organizations detect and alert on data anomalies in real-time, allowing data teams to identify and address issues before they impact business decisions. This is crucial for maintaining trust in the data, as inaccurate or unreliable information can lead to flawed analyses and misguided decision-making.
MC gained us visibility to our data and made it easier for us to communicate issues with our users
What do you like best about the product?
Easy UI, easy integration with other tools like slack/DBT/Tableau. Customer reps are also great- whenever we have a question, I know who to ask and I can reach out to the team directly
What do you dislike about the product?
Nothing much- there are a few features that we would like having, but I have flagged these to the product team and it seems like they are looking into it
What problems is the product solving and how is that benefiting you?
I am being alerted whenever my data breaks and it is easy to spot the impact of the data issue. Also, communicating the issues with our users is easy- they are part of the slack channel and are being alerted on time
MonteCarlo Usage Survey - WP Engine
What do you like best about the product?
The automated monitors that just work out of the box. While we leverage custom monitors quite a bit, having a set of automatically enabled monitors and alerts helps us move fast. MC has also been very easy to integrate into our existing stack. We also use the lineage feature quite a bit whiich measn we are in the platform daily. I also like the constant evolution of the UI and how the improvements always seem to be directed at the most valudable problems.
What do you dislike about the product?
There was a hicup in how we managed the transition to the new table model. Hats off you all that you worked with us to find a way to make it work. To offer a suggestion, having things like the usage report available before the decision was made would have been helpful. We had to go through a couple of iterations before we knew for certain what to look at to see our usage against our contract.
What problems is the product solving and how is that benefiting you?
We had a lagay data warehouse that was managed and maintained in silos by multiple teams. The primary use for MC was to offer out of the box solutiosn to both observe, identify and respond to data issues in a proactive way.
We are working with MonteCarlo to monitor the data health of our DWH platform.
What do you like best about the product?
Simple integration with data platform stack (in our case Snowflake,DBT,Looker)
Easy to use, no advanced technical skills required
Ability to monitor schema changes
Great catalog abilities (Lineage,search)
A single view of all data issues across the entire pipeline (DB to Looker)
Customer success and support are very responsive
Integration with Slack
Easy to use, no advanced technical skills required
Ability to monitor schema changes
Great catalog abilities (Lineage,search)
A single view of all data issues across the entire pipeline (DB to Looker)
Customer success and support are very responsive
Integration with Slack
What do you dislike about the product?
There is no option to save data errors in the database (only statistics and sample data can be obtained).
What problems is the product solving and how is that benefiting you?
Finding data issues in the DWH before they affect business users
impact analysis of data issues (using end to end lineage)
Monitoring DBT jobs
Schema changes (of raw data) alerts
impact analysis of data issues (using end to end lineage)
Monitoring DBT jobs
Schema changes (of raw data) alerts
MC - easy to use tool for monitoring data quality
What do you like best about the product?
Easy to use as a day to day monitoring tool. Great customer support, very responsive and always adding effective features.
What do you dislike about the product?
It does not easily output all erronous rows, the default is a sample.
There is no easy connection between one incident to the other.
There is no easy connection between one incident to the other.
What problems is the product solving and how is that benefiting you?
Our main issue is a daily feed of data from our partners which has a ton of errors. We set many monitors in MC, which alert us each day on new data incidents.
Devops Engineer Experience with Monte Carlo
What do you like best about the product?
It was very easy to integrate with AWS. Had very great experience with implementation team. I would like to emphasize on quick responses from customer support whenever we has questions or encountered issues.
What do you dislike about the product?
From integration and implementation point I had no issues but it would be great if redshift connectivity can be made through a role instead of local users
What problems is the product solving and how is that benefiting you?
Data Quality has improved
Data Observability with Monte Carlo is at a Whole New Level of Excellence
What do you like best about the product?
Monte Carlo has greatly enhanced our data observability capabilities.
It is a user-friendly platform, intuitive, and straightforward to integrate into our existing systems.
We've found their customer support to be commendable - quick to respond, helpful, and accommodating.
What stands out the most is the commitment to continuous improvement. The team regularly innovates and refines the product, keeping us engaged and optimistic about future enhancements.
It is a user-friendly platform, intuitive, and straightforward to integrate into our existing systems.
We've found their customer support to be commendable - quick to respond, helpful, and accommodating.
What stands out the most is the commitment to continuous improvement. The team regularly innovates and refines the product, keeping us engaged and optimistic about future enhancements.
What do you dislike about the product?
Despite the many positives, there are areas where improvement would be beneficial. Monte Carlo's integration with external tools such as PagerDuty and Opsgenie could be refined to add more functionality, it currently lacks some important features. Moreover, reducing noise in a large data lake could be easier, as it's quite a task at present.
What problems is the product solving and how is that benefiting you?
Monte Carlo enhances our data quality and observability, boosting transparency over our myriad of data assets. It alerts us to anomalies, allowing quick action, reducing troubleshooting time, and thus increasing our data's value.
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