Monte Carlo Data Observability Platform
Monte Carlo DataReviews from AWS customer
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Useful tool
What do you like best about the product?
Monte Carlo does a good job of detecting anomolies and alerting.
What do you dislike about the product?
There is a learning curve you have to get through. There is a lot of options that we don't utilize because we don't have time.
What problems is the product solving and how is that benefiting you?
Detects issues before the business, allowing us to address the issue before it is reported
Good Observability Tool for Enterprise Use
What do you like best about the product?
I like its ability to automate data quality monitoring and provide real-time visibility into data issues. The platform's comprehensive approach to data observability, with features like anomaly detection, lineage tracking, and proactive alerting, helps ensure the integrity of data pipelines and reduces downtime.
What do you dislike about the product?
The initial setup and integration with existing data infrastructure was time-consuming and complex
What problems is the product solving and how is that benefiting you?
MC helps in detecting data quality and faulty pipelines issues before it impacts downstream users
Go-to-tool for the Engineering team to automate Daily QA tasks
What do you like best about the product?
The tool helps us immensely in automating our daily QA efforts before sending out reports to the leadership team. The variety of checks it offers by default is incredible. With the help of machine learning, anomaly detection for any fields becomes easily possible. In addition to basic sanity checks, the tool also enables us to set up many custom monitoring. With integrations available for most ETL and visualization tools in the market, it serves as an all-in-one solution for data quality, lineage, and field dependency checks.
What do you dislike about the product?
Initially, the setup took some time, but I later realized that if things are set up correctly which is usually as a one-time activity, this tool becomes incredibly helpful. I did face a few challenges while setting up a custom list of tables to monitor, as Monte Carlo doesn't have a direct feature for this. However, I was assisted by the support team with alternative workarounds.
What problems is the product solving and how is that benefiting you?
Our Engineering team has a daily QA task that typically takes about 20-25 minutes. Once the QA is successful, the reports generated from the underlying tables are sent out to the leadership team. While we've automated many processes, it still required a substantial amount of time. After implementing Monte Carlo, it significantly reduced our QA effort, cutting the time down to just 10 minutes by setting up alerts to be triggered to our dedicated Slack channels. While we still perform some manual checks, we've automated 70% of our data quality and monitoring tasks with Monte Carlo. Additionally, Monte Carlo allows us to monitor many more aspects that we previously didn’t track.
i've been building on-premises and cloud based data platforms for more than 10 years
What do you like best about the product?
OOTB AI-driven monitoring capabilities offer an easy way to start gaining actianable insignts which become key drivers for better data quality and early data issues detection
What do you dislike about the product?
Some offerings (i.e. Monitors/Notifications As Code, Domains and Audiences, Monitored Tables) are pretty tricky to use and configure into a coherent data platform wide solution
What problems is the product solving and how is that benefiting you?
Monitoring data shema evolution, anomalies in data across my data platform, incomplete / corrupted data detection, business meaingfull alerts
Amazing tool for monitoring
What do you like best about the product?
I really like the visualization aspect of MonteCarlo, it's super helpful that we can check how the monitoring looks over time
additionally, you have a pretty great list of monitors that can cover 98% of needs
additionally, you have a pretty great list of monitors that can cover 98% of needs
What do you dislike about the product?
navigation sometimes can be tricky (Monitors sections)
sorry, it's hard to explain what exactly is tricky, I'm just caching myself struggling from time to time when I need to find monitors and understand what they are about
sorry, it's hard to explain what exactly is tricky, I'm just caching myself struggling from time to time when I need to find monitors and understand what they are about
What problems is the product solving and how is that benefiting you?
we added monitors with business rules and it helps us a lot
MC review
What do you like best about the product?
Keeping track of the state of the DWH and trace the lineage of tables and fields.
What do you dislike about the product?
The out of distribution notifications can be a bit overwhelming especially when the anomally is a biproduct of an already known issue in the DWH.
What problems is the product solving and how is that benefiting you?
Visibility into changes in the DWH that might be a second degree plus.
Powerful yet easy to use
What do you like best about the product?
Monte Carlo has an intuitive point-and-click interface that makes it easy to get up and running quickly. But at the same time the ability for more advanced configuration and code-based featuers makes it great for power users and for just about every data quality use case that we've faced at our mid-sixed business. We use it to monitor data quality but also to track the performance of our implementation of dbt and our dbt-native tests on quality. Even though Monte Carlo serves our needs there are still many features that we're excited to take advantage of in the future like circuit breakers.
What do you dislike about the product?
While it was easy to get the platform setup initially and get some preliminary alerting going, there was a bit of a learning curve before we began to feel like we were getting the most out of even the beginning features we were implementing.
What problems is the product solving and how is that benefiting you?
We primary use Monte Carlo for alerting around data quality issues. We rely heavily on Monte Carlo's native, machine-learning based tests as well as custom tests that we have written ourselves to alert members of our data team as well as the end-users of data products when potential data issues arises.
Secondarily, we use Monte Carlo within the data team to monitor the performance of our dbt models.
Secondarily, we use Monte Carlo within the data team to monitor the performance of our dbt models.
Great product backed with excellent support
What do you like best about the product?
MonteCarlo is a great tool for observing your data, I really like the automated monitors they provide as well as the functionality to build any number of custom monitors you want. In addition, they are super responsive to any concerns we have, and generally have been able to get in touch with someone within a couple of hours.
What do you dislike about the product?
The UI seems a bit dated, and can be daunting at first to get used to. I also wish they included visualizations within their slack alerts. I'm told this is on their roadmap.
What problems is the product solving and how is that benefiting you?
Monte Carlo is solving data observability for us. We are able to leverage their technology to build automated and custom monitoring on our data and ensure production tables are always hosting the correct data.
Good data quality checking tool, can be too techical for business users
What do you like best about the product?
ML powered tool, great in picking up data anomalies
What do you dislike about the product?
Can be challenging to tune noisy monitors. Harder for the business users to add their own metrics. No suggestions for monitor candidates. No error notification if monitor configuration is failing
What problems is the product solving and how is that benefiting you?
Anomalies in data which is super hard to catch 'manually'
A simple tool to track all aspects of data quality
What do you like best about the product?
I am thoroughly impressed with Monte Carlo's data observability tool. The monitoring features it provides are exceptional, enabling us to ensure data quality with ease. This tool has been a game-changer for our business, allowing us to confidently trust our data and make informed decisions.
Additionally, the exploration tools offered by Monte Carlo are top-notch. They provide deep insights into our data, making it easy to analyze and understand trends. These tools have been invaluable in uncovering hidden patterns and optimizing our data workflows. Especially when investigating data quality issues and getting to the root cause of a bug.
Overall, Monte Carlo has ensured our data is reliable and up to date. Its robust monitoring and exploration features have empowered us to maintain high data quality standards and drive our business forward. I would recommend Monte Carlo to any organization looking to enhance their data observability and ensure the integrity of their data.
Additionally, the exploration tools offered by Monte Carlo are top-notch. They provide deep insights into our data, making it easy to analyze and understand trends. These tools have been invaluable in uncovering hidden patterns and optimizing our data workflows. Especially when investigating data quality issues and getting to the root cause of a bug.
Overall, Monte Carlo has ensured our data is reliable and up to date. Its robust monitoring and exploration features have empowered us to maintain high data quality standards and drive our business forward. I would recommend Monte Carlo to any organization looking to enhance their data observability and ensure the integrity of their data.
What do you dislike about the product?
Sometimes the monitors can be noisy and cause a lot of false positives. It takes some effort to go in and ensure the monitors are tuned appropriately. For instance, row count anomalies can be noisy when a larger addition than expected occurs, but these are frequently false positive alerts.
I would also appreciate some more options for business logic monitoring. Often times stakeholders want to be able to see if sales of a specific product are down or shipping times are creeping up. These monitors are not so much about the quality of the data but the business understanding and it would be helpful to have a more robust and scalable way to integrate some sort business logic monitors into the product.
I would also appreciate some more options for business logic monitoring. Often times stakeholders want to be able to see if sales of a specific product are down or shipping times are creeping up. These monitors are not so much about the quality of the data but the business understanding and it would be helpful to have a more robust and scalable way to integrate some sort business logic monitors into the product.
What problems is the product solving and how is that benefiting you?
Monte Carlo is solving data pipeline issues and alerting us when there is bad data that is appearing in our tables.
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