Monte Carlo Data Observability Platform
Monte Carlo DataReviews from AWS customer
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Useful tool, needs to implemented with a plan
What do you like best about the product?
Monte Carlo is good at what it advertises - finding and alerting on data anomolies. It hooks up pretty seemlessly with dbt, Snowflake, and Tableau, and it does not take long to get monitors going. There are a wide array of tests and monitors that you can implement. There is also some out-of-the-box reporting on Snowflake performance, which can help you identify you most problematic/expensive queries. Monte Carlo also has cross-tool lineage tracking, which can be pretty useful even though the interface is not great.
What do you dislike about the product?
While Monte Carlo is easy to implement, I don't know that it's easy to implement _effectively_. Depending on the size and scope of your data, Monte Carlo will generate many alerts (you can customize how noisy each alert should be). But this leads to a set of questions: what are the things that you truly need to be alerted on? What tiers of severity are there for alerts? How do you handle a tier 1 alert compared to a tier 3 alert?
In my opinion these are really important questions to get value out of Monte Carlo. If you are too permissive, you will spend your entire day triaging Monte Carlo alerts. If you are too restrictive, it defeats the purpose of getting the toll in the first place.
The bottom line is, you will get the most value out of Monte Carlo if you have thought hard about how it fits into your existing Data Quality, Data Governance, and Triage processes.
In my opinion these are really important questions to get value out of Monte Carlo. If you are too permissive, you will spend your entire day triaging Monte Carlo alerts. If you are too restrictive, it defeats the purpose of getting the toll in the first place.
The bottom line is, you will get the most value out of Monte Carlo if you have thought hard about how it fits into your existing Data Quality, Data Governance, and Triage processes.
What problems is the product solving and how is that benefiting you?
Monte Carlo is really good at finding anomoloies in data (sometimes too good). This helps us find & fix problems faster. We set up monitors on both source and transformed data.
Pleasant experience using Monte Carlo
What do you like best about the product?
Monte Carlo helps identify all anomalies in the data proactively so that we can ensure that the quality of data is fit for purpose. It is fully customisable to make sure organisation specific needs are met.
What do you dislike about the product?
Updates are sometimes pushed without optimal notifications therefore we are sometimes blindsided by the impact of the change to the current processes, reporting etc.
What problems is the product solving and how is that benefiting you?
Pro-active visibility of data quality, DAG failures and freshness. I am able to periodically view and extract dashboards for reporting purposes.
An excellent data quality monitoring tool
What do you like best about the product?
Easy to set up
Quick time to value
Simple yet powerful alerting
Sensible default data tests
Reliable
Easy to build my own business logic tests
Alerts are easy to tune
Quick time to value
Simple yet powerful alerting
Sensible default data tests
Reliable
Easy to build my own business logic tests
Alerts are easy to tune
What do you dislike about the product?
Some pieces of the UI are a little rough
What problems is the product solving and how is that benefiting you?
Monte Carlo helps prevent outdated/innacurate data from being sent to decision makers. It does this by making it easy to know when there is a problem and providing pointers for remidiation.
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.
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.
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