Monte Carlo Data Observability Platform
Monte Carlo DataReviews from AWS customer
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Full Quality Coverage
What do you like best about the product?
What I like most about Monte Carlo is that it raises all data issues in the system. No anomaly goes undetected.
Also, the ability to view table and field lineage is very helpfull.
Also, the ability to view table and field lineage is very helpfull.
What do you dislike about the product?
Monte Carlo can provide many false alerts. User has to fine tune the algorithm in order for Monte Carlo to yield better results.
What problems is the product solving and how is that benefiting you?
Monte Carlo provides ongoing built in data quality monitoring with volume and freshness anomalies. In addition you can create custom monitors to better suite specific needs.
In cases where data issues are raised by Monte Carlo you can use the linage tool to better know which models and reports were affected by this issue.
In cases where data issues are raised by Monte Carlo you can use the linage tool to better know which models and reports were affected by this issue.
Monte Carlo - our eyes on the data piplines.
What do you like best about the product?
Real easy to use product , focuses on the right areas , uses AI / ML for recommendations and tries to find the right balance between alerting and reducing noise.
What do you dislike about the product?
more connectivity to our current ETL tool to complete the whole picture.
What problems is the product solving and how is that benefiting you?
Finds us data issues that we will never see before our reports / dashboard users.
Great tool for Enterprise Data Observability
What do you like best about the product?
Out-of-the-box machine learning monitors that check for freshness, volume, and schema changes are awesome!
What do you dislike about the product?
To be very honest, it's the best technology I have used for data observability and data quality checks at scale. But if I have to point out one thing - it would be those additional features that come with the integrations. For eg - MC tries to show traces of our airflow integration at multiple places but at some places, I don't find it accurate. Same thing goes with dbt integration.
What problems is the product solving and how is that benefiting you?
This is one of my favorite technology I have ever used. I really love it's out-of-the-box ML monitors that provide us alerts whenever an anomaly is detected and in majority of the cases it's a true positive. Data quality is critical for any organization and being able to manage it across the organization without spending a lot of time on it is something really great. Monte Carlo empowers us to do this in the most efficient and optimized way. It has a wide range of standard monitor templates using which we can quickly create table monitors and also provides customization to the level where we can define monitors using YAML code! It's helping us detect any data quality issues very quickly and also provides a nice lineage and the impact analysis.
Nice and useful software
What do you like best about the product?
I think the alerts are really valuable. Also the summary of the monitors give you a good understanding of what is happening with your tables. I use a lot the table lineage feature when I'm looking at a new table, it is easy to understand the dependencies of it, and how important it is.
What do you dislike about the product?
When I see the summary page, I can only see the last 30 days of the monitors' history. It is helpful but I'd really like to have more history, so I can better understand the incidents and check when some trends started.
Also, I activated the field health monitors for some important tables; however, the it is sending a lot of false positives alerts, generating alert fatigue
Also, I activated the field health monitors for some important tables; however, the it is sending a lot of false positives alerts, generating alert fatigue
What problems is the product solving and how is that benefiting you?
It makes it easy to have a general look of the tables, and it also automates the monitoring so that you can be safe knowing that if anything strange happens, you'll have Montecarlo to alert you.
I’m a BI Developer in MoonActive, using Mone Carlo to observe my company’s data
What do you like best about the product?
I’ll say few positive things:
1. The UI is very good, easily can create custom alerts and to investigate the data
2. The ability to connect MC with many alerts pipes such as Slack, mail
3. The sensitivity feature that allow us as data users to control when MC alerts will take action
1. The UI is very good, easily can create custom alerts and to investigate the data
2. The ability to connect MC with many alerts pipes such as Slack, mail
3. The sensitivity feature that allow us as data users to control when MC alerts will take action
What do you dislike about the product?
1. Sometimes the default alerts sensitivity is too high, and then I get spam alerts (for example added 10K rows, usually 10.5K rows). I’ll prefer that the default will be less sensitive
2. The custom alerts title to Slack requires 1 row, which requires aggregation of the query into a single row. It would be more convenient if MC would already take the column and collapse it into a single row automatically w\o using SQL function
2. The custom alerts title to Slack requires 1 row, which requires aggregation of the query into a single row. It would be more convenient if MC would already take the column and collapse it into a single row automatically w\o using SQL function
What problems is the product solving and how is that benefiting you?
1. Automatic monitoring of my DB even when new tables are added without the need for manual intervention
2. The ability to automatically identify anomalies in the data
3. The alerts are dynamic - important tables will be marked with a star, data that has been sorted out will be marked with ״normalized״. This really helps me pay attention and emphasize important things
2. The ability to automatically identify anomalies in the data
3. The alerts are dynamic - important tables will be marked with a star, data that has been sorted out will be marked with ״normalized״. This really helps me pay attention and emphasize important things
Montecarlo: An amazing Observability platform
What do you like best about the product?
Monitoring errors, alerts is something i use a lot, able to group them quickly search it out.
Implementation with sqls is a bit not too complicated for non sql users.
I use Montecarlo especially for on calls.
Customer support from Mark is really good
Implementation with sqls is a bit not too complicated for non sql users.
I use Montecarlo especially for on calls.
Customer support from Mark is really good
What do you dislike about the product?
I would like to seach alerts based on statements
and cluster alerts across sites.
Also need Monte carlo to support default ML drift detection
and cluster alerts across sites.
Also need Monte carlo to support default ML drift detection
What problems is the product solving and how is that benefiting you?
Issues with snowflake tasks, queries , Jobs
Data Quality Monitoring
What do you like best about the product?
Setting up the alerts, integration and dashboard is easy to use.
What do you dislike about the product?
It takes time to keep on tuning for right param threshold to get the monitor right
What problems is the product solving and how is that benefiting you?
Mainly to keep an eye on the quality of data/features
Great product, clean interface, top notch support
What do you like best about the product?
The interface is very clean an intuitive. Deep integrations give me an overview of our data and pipelines.
What do you dislike about the product?
Some data with high variability is not yet well understood by the ML volume and freshness monitors
What problems is the product solving and how is that benefiting you?
We are able to maintain a high standard of data quality thanks to the monitoring of our ingestions and transformations.
The asset views are useful for anyone who wants to get a feel of how the data changes over time, the volumes etc.
The asset views are useful for anyone who wants to get a feel of how the data changes over time, the volumes etc.
Monte Carlo lets you enforce your system's invariants
What do you like best about the product?
My team has been using Monte Carlo for a few years now and we've come to rely on it for ensuring that our data is what we think it is, which has opened the door for us to use different architectures then we could have otherwise.
As I said in the title, it lets us encode and enforce the invariants we see in our systems without requiring endless handwritten batch tasks or overloading shared resources. Running these queries on our OLTP database would be hugely impractical, if it were even possible, and running them on our data warehouse manually would be a joke. But allowing MC to run them daily means that we can easily add as many as we want and know that, unless we're being alerted, our expectations for the data are accurate.
As I said in the title, it lets us encode and enforce the invariants we see in our systems without requiring endless handwritten batch tasks or overloading shared resources. Running these queries on our OLTP database would be hugely impractical, if it were even possible, and running them on our data warehouse manually would be a joke. But allowing MC to run them daily means that we can easily add as many as we want and know that, unless we're being alerted, our expectations for the data are accurate.
What do you dislike about the product?
Some aspects of the UI are a bit unclear. For example, when making new alerts, syntax errors are not communicated at all, and there's an inexplicably short timeout, which can make testing some larger queries impossible.
What problems is the product solving and how is that benefiting you?
Ensures that our data is in the state we expect. For example, we have a table that's supposed to be in sync with another in a specific way, but that we need to maintain manually. Monte Carlo ensures that, if our code makes a mistake, we can fix it before our batch tasks run with incorrect data. We also have all kinds of SLAs with our partners that Monte Carlo helps us meet by checking daily that all our outputs have been created on time.
Monte Carlo Review
What do you like best about the product?
Querying is very easy and follows SQL. Alerting from queries is a cool use case. Dashboards help track metrics easily.
What do you dislike about the product?
UI is a little complicated and could be prettier.
What problems is the product solving and how is that benefiting you?
We are able to find issues with data quality or logical flaws automatically, then alert engineering asap to resolve the issue.
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