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Up and running with data observability across production.
What do you like best about the product?
Great POC process, impressed over competitor products with the smoothness of the POC. The easiest product to get up and running with basic observability checks. Has been making improvements to the product relatively quickly. The overall direction of the product aligns well with our needs and business direction. The team is a pleasure to work with, open to feedback, and willing to have critical discussions. Many of the recent improvements have cleared up our team's most urgent needs for the product. All of these improvements have happened within 6 months of our implementation.
What do you dislike about the product?
Could use some maturation in the onboarding process, more hands-on, technical, and industry-specific. There were many to-be-desired features when we first implemented. Many of those features have now been implemented, which is within six months of starting our implementation. More transparency into the product roadmap, what features are getting worked on, what some estimated release dates are, and what the highly rated/asked-for features are. Persistent UX/UI issues that could use improvement have not been fixed quickly.
What problems is the product solving and how is that benefiting you?
Monte Carlo has allowed us to implement observability on our entire product analytics stack. From ELT, to Data Lake, to transformations, to Data Warehouse, to Reporting/Dashboarding. We have also started to dive into deeper Data Quality monitoring as well. This allows our centralized data team to react faster, notice issues before the business does, route and notify the correct business and technical users about anomalies, and make sure our product analytics environment is running as reliabily as possible.
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Using Monte Carlo for observability of data pipelines
What do you like best about the product?
Monte Carlo enables us to monitor our data pipelines and alerts us if we haven't received an expected data refresh from our external partners. For example, a downstream user was concerned that partner data was stale; we quickly confirmed that while the pipeline continued to refresh, new records were not being received. Sharing this information visually via Monte Carlo with our downstream users is also very effective. Monte Carlo provides alerts via Slack which we use to keep relevant users informed. This provides an additional level of transparency and data ownership for our business users.
What do you dislike about the product?
Because Monte Carlo provides such breadth and depth of information, it can take a bit to get up to speed on using the product. I have found their production tutorials helpful, but even more beneficial to have a session with your customer success manager. It's also essential to manage notifications in relevant channels so they don't become noise.
What problems is the product solving and how is that benefiting you?
We use the domain feature to alert business users to any upstream issues in source data. Often this may be a problem not with the data pipeline, but the data provider; understanding this allows the business stakeholder to take quick action. Custom monitors provide alerts on key data fields pinpointing missing or inaccurate data before it impacts downstream BI.
Invaluable tool and exceptional customer support
What do you like best about the product?
Monte Carlo is a gamechanger for our company and invaluable for our mission to improve data quality. The built in anomaly detection monitors are super helpful, and the custom monitors are perfect for alerting us to issues that are particular to our data sets. We rely heavily on the data lineage and impact radius analysis to figure out where data is coming from, going to and who is using it. I can't imagine running a data team without this tool.
What do you dislike about the product?
Monte Carlo is very close to having a fully functional data catalog that would obviate the need for another tool. I'd love to see that feature fully fleshed out.
What problems is the product solving and how is that benefiting you?
Monte Carlo is a key part of our data certification and governance program. We can't have confidence in our reports if we don't know about underlying data issues. Monte Carlo gives us deep insight into data quality, data anomalies and changes in the data that would otherwise take the team a long time to find, or worst case, our stakeholders discover when looking at a report.
Monte Carlo enables a quick start and deep insights into Data Reliability
What do you like best about the product?
Monte Carlo delivers a 'low water mark' in Data Reliability with little time investment. We are up to speed across our main BigQuery datasets in a matter of weeks and have enhanced our Incident Management and Root Cause Analysis abilities considerably. Monte Carlo is also well liked by the Engineers as it enables a high degree of automation
What do you dislike about the product?
We can limit which datasets are scanned - and their associated license cost - at the GCP Project and Dataset level, but ideally we'd like to be able to set this at the individual table level.
Not really a dislike, butwe would like support for Kafka streams as that would enable Observability even closer to the source.
Not really a dislike, butwe would like support for Kafka streams as that would enable Observability even closer to the source.
What problems is the product solving and how is that benefiting you?
We currently have a fragmented approach to Data Quality testing across the Organisation. Teams are responsible for their own quality, and those that do create monitoring do so using different platforms and tools and rarely publish metrics consistently. We are beginning to roll out Monte Carlo across all our Data Teams. Monte Carlo delivers a high degree of consistency across the organisation enabling us to get a pitcure of overall reliability and generate some metrics that will allow us to set targets to improve quality across our entire data estate.
In addition - and not initially a driver - Monte Carlo helps us with its incident management, ensuring that issues are owned and categorised effectively.
And a further benefit of Monte Carlo are the Insights into the tables its scanning - we've already identified objects that we didn't think were important, but are referenced multiple times in pipelines and the usage reports have helped us prune unused tables
I should also call out both Monte Carlo's pre-sales/ Proof of Concept support and Customer Onboarding - both of which have been excellent. Their customer onboarding in particular is probably the best I've encountered.
Monte Carlo is not cheap, but is worth the money!
In addition - and not initially a driver - Monte Carlo helps us with its incident management, ensuring that issues are owned and categorised effectively.
And a further benefit of Monte Carlo are the Insights into the tables its scanning - we've already identified objects that we didn't think were important, but are referenced multiple times in pipelines and the usage reports have helped us prune unused tables
I should also call out both Monte Carlo's pre-sales/ Proof of Concept support and Customer Onboarding - both of which have been excellent. Their customer onboarding in particular is probably the best I've encountered.
Monte Carlo is not cheap, but is worth the money!
The most essential piece of our Data Quality Management
What do you like best about the product?
I love that I'm able to not only receive notifications but generate reporting metrics that describe the state of data processes without manual work.
What do you dislike about the product?
For tables that are updated in a non-deterministic way, it's hard to configure alerting properly.
What problems is the product solving and how is that benefiting you?
We catch issues that we would not have known about
We can quickly troubleshoot root causes in data sets
We can report to the business on the state of our data processes honestly and accurately
We can quickly troubleshoot root causes in data sets
We can report to the business on the state of our data processes honestly and accurately
Monte Carlo is a powerful platform for data discovery, lineage, and quality management.
What do you like best about the product?
I love the built-in monitors and alerts. It is beneficial that many built-in monitors, like freshness and volume, don't require configuration. The Machine learning ability of the tool does an excellent job of learning the cadence and size of the data with no effort required. Monte Carlo offers an extensible and flexible set of tools to customize alerts for data quality.
The data lineage features of Monte Carlo are impressive and easy to use. Being able to trace data from S3 storage to Tableau is powerful.
Integrating with DBT makes finding data easier for our product teams. They don't need to be experts on the data to discover what they need.
The data lineage features of Monte Carlo are impressive and easy to use. Being able to trace data from S3 storage to Tableau is powerful.
Integrating with DBT makes finding data easier for our product teams. They don't need to be experts on the data to discover what they need.
What do you dislike about the product?
There is so much that Monte Carlo has to offer that the UI can be intimidating. Some additional handholding, tooltips, or other visual cues could be helpful to someone who is less technically included or doesn't have time to read the documentation.
What problems is the product solving and how is that benefiting you?
Monte Carlo continually monitors our data warehouse to identify data anomalies. This tool has allowed my small team to scale across many data pipelines. Data Operations, Engineers, and stakeholders know when there are issues with the data.
Monte Carlo- A+ tool for Data Observability
What do you like best about the product?
1. We can pick any monitor from Monte Carlo's list based on our requirements and set up notifications from various channels such as Slack/Teams or emails.
2. Out-of-the-box features that detect schema changes and data volume is fantastic.
2. Out-of-the-box features that detect schema changes and data volume is fantastic.
What do you dislike about the product?
I don't dislike the product so far, but there are cases when people might get false negative alerts if you don't set up the notifications properly.
What problems is the product solving and how is that benefiting you?
Monte Carlo is helping us to solve the biggest problem of reducing data downtime by alerting various teams who owns the data pipeline.
Robust platform for managing Data Observability and Quality needs
What do you like best about the product?
Great tool for monitoring Data Quality of new as well as already existing tables. Love the continuous addition of new features which further enable end to end Data Quality checks!
What do you dislike about the product?
At some time in future it would be great to have a feature which would enable Data Quality checks across ETL workflows i.e. to validate if data from source is loaded as expected in the target.
What problems is the product solving and how is that benefiting you?
Monte Carlo alerts whenever data looks like it is not in the expected shape or format which then allows to fix the issues before they impact end users of the data.
"Safe and Data Trust Data Observability Platform"
What do you like best about the product?
This platform is very easy to use and implement.Its a reliable application to manage
and analyse the data.
It provides advanced machine learning capabilities and algorithms to identify and resolve the data outliers and anamolies.
and analyse the data.
It provides advanced machine learning capabilities and algorithms to identify and resolve the data outliers and anamolies.
What do you dislike about the product?
There is no problem with this software,It's working fine with me.
What problems is the product solving and how is that benefiting you?
It is very much useful in data quality monitoring.It is very easy to implement
By this software we can predict the problem earlier and solve the issues at it's root.It saves lot of time when it compared to other software.
By this software we can predict the problem earlier and solve the issues at it's root.It saves lot of time when it compared to other software.
Reliable application for managing data
What do you like best about the product?
Monto Carlo application helped me to solve the large data management. It's a reliable application to analyse the data manage the data and reporting the data and making decisions based on the data
What do you dislike about the product?
There is nothing to dislike the Monte Carlo as it's used to manage large amount of data there will be some limitations and monte Carlo will evolve to over come those limitations
What problems is the product solving and how is that benefiting you?
Monto Carlo helped me to solve large data driven decision making and also monitoring of the data. Analzing and reporting of the data made easy in the Monte Carlo
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