Sold by: Monte Carlo DataÂ
Deployed on AWS
Data breaks. We ensure your team is the first to know and the first to solve with end-to-end data observability.
Overview
As businesses increasingly rely on data to power digital products and drive better decision making, it's mission-critical that this data is accurate and reliable. Monte Carlo's Data Observability Platform is an end-to-end solution for your data stack that monitors and alerts for data issues across your data warehouses, data lakes, ETL, and business intelligence. The platform uses machine learning to infer and learn your data, proactively identify data issues, assess its impact, and notify those who need to know. By automatically and immediately identifying the root cause of an issue, teams can easily collaborate and resolve problems faster. Monte Carlo also provides automatic, field-level lineage and centralized data cataloging that allows teams to better understand the accessibility, location, health, and ownership of their data assets, as well as adhere to strict data governance requirements.
Highlights
- Detect: Detect data quality issues before your stakeholders at each stage of the pipeline
- Resolve: Resolve data issues with out-of-the-box root cause and impact analysis, including end-to-end field-level lineage
- Prevent: Prevent data downtime proactively across your stack
Details
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Deployed on AWS
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Pricing
Pricing is based on the duration and terms of your contract with the vendor, and additional usage. You pay upfront or in installments according to your contract terms with the vendor. This entitles you to a specified quantity of use for the contract duration. Usage-based pricing is in effect for overages or additional usage not covered in the contract. These charges are applied on top of the contract price. If you choose not to renew or replace your contract before the contract end date, access to your entitlements will expire.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/12 months | Overage cost |
|---|---|---|---|
Monte Carlo Credit | Monte Carlo's Data Observability Platform Credit | $50,000.00 |
Vendor refund policy
All fees are non-cancellable and non-refundable except as required by law.
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Delivery details
Software as a Service (SaaS)
SaaS delivers cloud-based software applications directly to customers over the internet. You can access these applications through a subscription model. You will pay recurring monthly usage fees through your AWS bill, while AWS handles deployment and infrastructure management, ensuring scalability, reliability, and seamless integration with other AWS services.
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Support
Vendor support
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Customer reviews
0 ratings
0 AWS reviews
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3 external reviews
Star ratings include only reviews from verified AWS customers. External reviews can also include a star rating, but star ratings from external reviews are not averaged in with the AWS customer star ratings.
Pharmaceuticals
Automated and evolving insights on your Data Mesh - Data Products
Reviewed on Nov 07, 2023
Review provided by G2
What do you like best about the product?
They are innovative and every month, I'm getting a new feature on my dashboard. The intergation with other Data Engineering tools is great. Monitoring as a Code or UI based monitoring management is very easy. The team is very responsive in term of customer support either for new feature or bug fixes.
What do you dislike about the product?
The naming conventions are a bit un orthodox or confusing at times.
I'm waiting for more evolved dashboarding features.
I'm waiting for more evolved dashboarding features.
What problems is the product solving and how is that benefiting you?
I'm able to monitor data availablity and qulaity matrics very easily. Do get alerts and automated management on the same.
- It's help me generate/capture SLIs on My Data Products and share them with stakeholders and potential consumers of my data.
- It's help me generate/capture SLIs on My Data Products and share them with stakeholders and potential consumers of my data.
Prathik Rokhade
Provides centralized data observability features and has an easy-to-use user interface.
Reviewed on Aug 31, 2023
Review provided by PeerSpot
What is our primary use case?
Monte Carlo works as a centralized data tool. We use it for data observability and anomaly detection, which helps identify issues and changes in data flows.
What is most valuable?
The product allows us to segment data into domains and categories. It makes organizing work easier based on its relevance to specific projects and teams. Additionally, the orchestration layer within the tool plays a vital role in streamlining data processes.
What needs improvement?
For anomaly detection, the product provides only the last three weeks of data, while some competitors can analyze a more extended data history. This feature needs improvement. Its price could be a bit competitive compared to competitors offering similar services.
For how long have I used the solution?
We have been using Monte Carlo for three years.
What do I think about the scalability of the solution?
The product is scalable. However, they could improve the pricing and provide more cost-effective ways of scaling.
How are customer service and support?
They offer efficient customer service. They provide essential documents, feedback, and solutions. They set up a meeting with us whenever we require more information.
How would you rate customer service and support?
Positive
How was the initial setup?
The product's initial setup is in a daily improvement stage, deploying new plugins for upstream and downstream resources. It takes 25 minutes to complete. The process involves integrating with third-party services for Single Sign-On (SSO). It requires only one executive for maintenance as it has easy-to-use navigation and user interface.
What's my experience with pricing, setup cost, and licensing?
The product has moderate pricing.
What other advice do I have?
The product has centralized nodes and is a pioneer in the data observability domain. It has helped a lot in investigating system issues. It also saves a lot of time in identifying issues by improving data traffic.
I rate Monte Carlo a nine out of ten.
Vishal S.
Create an automated proactive fail-safe and data trust using the Monte Carlo Data Observability Platform.
Reviewed on Mar 15, 2023
Review provided by G2
What do you like best about the product?
Get Value for Money (ROI) on investment immediately
Generate Data Trust
Very Easy to Implement
Rich Integration with Tools
Generate Data Trust
Very Easy to Implement
Rich Integration with Tools
What do you dislike about the product?
Only available for SAAS Platforms and Dashboard Tools
Workflow Access Control is not yet available
Workflow Access Control is not yet available
What problems is the product solving and how is that benefiting you?
Proactive Data Monitoring
Certifying Data - Data Trust
Data Lineage to show the full impact of Anomaly
Certifying Data - Data Trust
Data Lineage to show the full impact of Anomaly