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A game changer in data quality
What do you like best about the product?
Monte Carlo gives us peace of mind when it comes to the quality of our data. It has been instrumental in standing up a data quality initiative, and has helped us catch incidents that previously would have taken us days, or even weeks, to notice. The Monte Carlo team is responsive and helpful, and has always responded promptly when we have questions or suggestions.
What do you dislike about the product?
Monte Carlo is not very good at detecing seasonal data beyond daily seasonality. We have tables that update weekly or monthly, and it struggles to detect patterns in this data. I also wish it were a bit easier to manage ingestion at the table level; we are billed per ingested table, and it would be nice to easily turn ingestion on/off for tables rather than schemas.
What problems is the product solving and how is that benefiting you?
Monte Carlo monitors our data and helps us detect changes in our raw data that we may struggle to notice otherwise. This benefits us greatly because we can preserve the quality of our data in real-time, rather than having to make adjustments later or release inaccurate data to our customers.
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Doing a Great Job of Monitoring
What do you like best about the product?
It provides a user friendly was to monitor our enviroment
What do you dislike about the product?
Have not run into any issues at the moment
What problems is the product solving and how is that benefiting you?
It has helped with monitoring an disscrepencies in our processes
Great tool for monitoring systems
What do you like best about the product?
MC makes it really easy to set up automated and custom alerts on core systems. It has a lot of out-of-the-box monitors that we rely on heavily.
What do you dislike about the product?
The large number of potential monitors can cause some alert fatigue, and Monte Carlo can be better at helping us parse out which alerts are more critical.
What problems is the product solving and how is that benefiting you?
It helps various teams in our company create their own alerting without much support from our team.
Data Observability and so much more
What do you like best about the product?
Having views into Data Lineage, Table Schema and Table Usage that are always up to date; always works with our tech stack without issue; wonderful support from multiple members of the team, from integration through Product touchpoints about new features
What do you dislike about the product?
Tuning for signal to noise; alerting does not leverage status updates to suggest monitors can be decommissioned
What problems is the product solving and how is that benefiting you?
Identifying schema changes that require additional, downstream action; in support of incident analysis, quickly identifying a change that may have caused a downstream issue; Data Lineage, providing a comprehensive view from data warehouse asset to our visualization layer; alerting external teams via Slack alerts to facilitate self service
Pie Insurance using Monte Carlo for monitoring Enterprise Data Warehouse
What do you like best about the product?
Ease of configuration, user-friendly UI, helpful support staff, data exploration tools, data set analysis and value index
What do you dislike about the product?
The automated monitoring and alerting has not been very helpful for our specific use cases. We have configured the notifications to only notify for the top 10% of our data sets which has helped
What problems is the product solving and how is that benefiting you?
Monitoring data from an external perspective benefits us by giving us extra confidence that data is flowing as expected
Superb
What do you like best about the product?
Monte Carlo are one of the few vendors focused on modern data quality. A cursory review of quality assurance testing approaches reveals a sole interest in software systems. Very little testing strategies have been built around data-first systems. Monte Carlo is blazing new paths into data quality on modern data processing systems.
What do you dislike about the product?
Monte Carlo is still building operational workflows on their product. They have a good system and are developing their position on data quality.
What problems is the product solving and how is that benefiting you?
Data quality. Automated testing, quality KPIs, and quality operations.
Centralized Observability
What do you like best about the product?
The out of the box features, that can be helpful without a lot of guidance.
What do you dislike about the product?
It's not a dislike, but the work that needs to be put in. To get the most out of the product, working with the MC team to specific nuances of data, you can't get away with this for really any product. The better MC has an understanding of the data, the better the value.
What problems is the product solving and how is that benefiting you?
For data engineering, MC is our primary Production Monitoring tool. Pre-emptive alerts before they the errors are triggered, Alerts to reinforce analysis, to be sure you know the problems as early as possible.
Monte Carlo is the all seeing eye for our data
What do you like best about the product?
Its so helpful to have a tool that is constantly monitoring our data and lets us know when something suspicious happens. Countless times Monte Carlo has alerted us to an issue in the data before anyone else was aware, some of them quite high prority!
I really appreciate the customisability of Monte Carlo, you can set up your own custom sql tests meaning you can test just about anything you want. But conversely I also like the out of the box tests that Monte Carlo provides, meaning we don't need to constantly be setting up new custom tests for every table, the default tests provide a really good baseline for the 'health' of a table.
Finally the support we get from Monte Carlo is great. If I'm unsure how to do a particular thing or how best to implement a test I know they are just a question away and will be super supportive and helpful!
I really appreciate the customisability of Monte Carlo, you can set up your own custom sql tests meaning you can test just about anything you want. But conversely I also like the out of the box tests that Monte Carlo provides, meaning we don't need to constantly be setting up new custom tests for every table, the default tests provide a really good baseline for the 'health' of a table.
Finally the support we get from Monte Carlo is great. If I'm unsure how to do a particular thing or how best to implement a test I know they are just a question away and will be super supportive and helpful!
What do you dislike about the product?
I think, perhaps due to the amount of features and customisability Monte Carlo provides, sometimes the UI can be a little confusing. Setting up basic tests can be pretty straight forward but there are many different test types available and sometimes that can feel like there is a steep learning curve to using the platform.
However Monte Carlo does provide a MC university with lots of guides so I and my team could be utilising that more!
However Monte Carlo does provide a MC university with lots of guides so I and my team could be utilising that more!
What problems is the product solving and how is that benefiting you?
Our team is fairly small and we have a lot of data. It would be nigh impossible for us to continually monitor the data we are receiving and thats where Monte Carlo really helps us. The volume and freshness alerts are so valuable to let us know we are being sent the data that we would expect. A few times we have been alerted by Monte Carlo to find that there has been an error upstream and we are not receiving business crititcal data into our data warehouses, and this was before anyone else noticed.
Monte Carlo's audience feature means teams can set up their own monitors on their own data and be alerted in their own slack channel, this means we, as the centralised data team, aren't a bottle neck for teams to address data issues with their own pipelines.
Monte Carlo's audience feature means teams can set up their own monitors on their own data and be alerted in their own slack channel, this means we, as the centralised data team, aren't a bottle neck for teams to address data issues with their own pipelines.
A Robust Data Observability Tool
What do you like best about the product?
The tool excels in providing monitoring and automated data quality checks, which are crucial for maintaining data integrity. Its intuitive UI, clear, actionable insights, data lineage, and anomaly detection features are highly effective at identifying issues before they impact decision-making. The integration with various data sources is seamless, making it easy to incorporate into existing data ecosystems. Additionally, Monte Carlo’s proactive alerting system ensures that data issues are addressed promptly, enhancing overall data reliability.
What do you dislike about the product?
The platform’s pricing structure imposes limitations on the number of integrations, which can be restrictive and may affect its overall utility for teams with diverse data environments
What problems is the product solving and how is that benefiting you?
Monte Carlo has consistently and reliably alerted us to data integration issues, helping us ensure that problems are detected and addressed before they impact downstream systems and decision-making.
Making Data Observability Simple
What do you like best about the product?
At my company we have only scratched the surface of this best-in-class data observability tool and have found it incredibly easy to use and build monitors. We were able to get our first monitors running within days of the initial setup which is a credit to the onboarding team that worked with us through the process. We can schedule monitors that alert us to time sensitive data quality issues which allows us to triage and correct issues before they escalate. Monte Carlo offers great out of the box monitors with the option of creating our own SQL monitor’s as well. This gives us the ability to implement more nuanced and complex monitors which have improved our data quality in various areas.
What do you dislike about the product?
Nothing comes to mind and the issues we have encountered have been addresses quickly by the support team.
What problems is the product solving and how is that benefiting you?
We have a small data team so having a tool that quickly highlights data issue before they turn into major issues is paramount. For example, the data quality of our master data is extremely important to our sales team, so we run various check in Monte Carlo every morning to make sure everything is in order before they start there day.
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