Monte Carlo Data Observability Platform
Monte Carlo DataReviews from AWS customer
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Powerful tool that's key for data quality
What do you like best about the product?
The features are diverse and it's a smart tool with the ML integration, and the amount of information available is very useful. It integrates well with Slack and notifies us quickly of issues. We monitor it daily. Our customer support contact is excellent.
What do you dislike about the product?
The UI is occasionally difficult to navigate when I want to implement a specific change to a monitor. I'm not sure how this could be changed though.
What problems is the product solving and how is that benefiting you?
Data quality, we can quickly identify when something unexpected has changed in our database and can quickly rectify before it has downstream consequences.
It is a great tool for data observability
What do you like best about the product?
The UI is very user friendly and intuitive. Ease of Integretion to various channels/sources.
What do you dislike about the product?
Few features need to be more stable. For example tagging must be simplified, usage of secondary query engine to test and create monitors etc.
What problems is the product solving and how is that benefiting you?
Having a centralized platform for monitoring and managing all the data anamolies is great.
Easy and usefull Data quality tool
What do you like best about the product?
Easy to set up base monitors.
The tool is very flexible in settings, you can implement almost any ideas for monitoring.
Customer success team are very helpful.
The tool is very flexible in settings, you can implement almost any ideas for monitoring.
Customer success team are very helpful.
What do you dislike about the product?
Low support of Databricks, a lot of features availible only on Snowflake or BigQuery.
What problems is the product solving and how is that benefiting you?
Data quality monitoring
Powerful data quality product with a passionate and dedicated team behind it
What do you like best about the product?
The Monte Carlo account team has been extremely supportive and dedicated to getting the tool installed and working as best we can.
It is simple to create new data quality rules, and has been easy to get started. There are many data quality rule options that allow us to implement a variety of validation rules very easily.
It is simple to create new data quality rules, and has been easy to get started. There are many data quality rule options that allow us to implement a variety of validation rules very easily.
What do you dislike about the product?
The billing method of paying per table means that we have to be selective about where we use the tool.
What problems is the product solving and how is that benefiting you?
Monte Carlo helps us monitor our data estate in order to detect data quality issues before our customers report them.
Monte Carlo does help prevent incidents by highlighting data quality problems
What do you like best about the product?
I was initially skeptical about the value Monte Carlo could bring to our team, but since we started using it, it has actually helped us prevent a few incidents by highlighting data quality problems in upstream datasets. Previously, we would only discover such problems after receiving complaints from our consumers, which demanded significantly more time and effort to address.
What do you dislike about the product?
The team doesn't like the false alerts raised by Monte Carlo, which distract engineers. We try to solve this problem by utilizing different priorities, but it doesn't completely solve this issue.
What problems is the product solving and how is that benefiting you?
The main business problem is a lack of trust in our data, which means when something breaks and data becomes incorrect, we will only know about it when our customers come to us.
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
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