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Monte Carlo description
Monte Carlo is a software platform designed to ensure your data is accurate and reliable. It monitors your data systems 24/7, using machine learning to automatically detect any data errors or inconsistencies. When problems arise, Monte Carlo immediately alerts the right people and helps them pinpoint the root cause, minimizing disruptions to your business. It also helps you understand the health of your data and provides a clear picture of its journey within your systems. This makes it easier for everyone to find, trust and use data effectively.
What companies are using Monte Carlo?
Who is Monte Carlo best for
Monte Carlo is a data reliability platform ideal for data engineers and analysts. It provides automated data quality monitoring, alerting, and lineage tracking to ensure data accuracy. Users praise its out-of-the-box monitoring and customer support. However, some find the UI confusing and experience alert fatigue. Monte Carlo is best for companies prioritizing data-driven decision-making.
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Best for medium to large enterprises seeking reliable data quality.
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Ideal for data-driven industries reliant on accurate data for decision-making.
Monte Carlo features
| Supported Monte Carlo actively monitors and improves data accuracy, completeness, and consistency. |
| Supported Monte Carlo supports data lineage, enabling tracking of data origin, transformations, and destinations. |
| Supported Monte Carlo supports observability by monitoring data pipelines and identifying data quality issues. |
We evaluate the sentiment that users express about non-functional aspects of the software
Value and Pricing Transparency
Customer Service
Ease of Use
Reliability and Performance
Ease of Implementation
Scalability
Monte Carlo reviews
We've summarised 214 Monte Carlo reviews (Monte Carlo G2 reviews) and summarised the main points below.
- Out-of-the-box monitoring is very useful
- Excellent customer support - very responsive and helpful
- Slack integration for notifications
- Lineage feature is very useful for identifying downstream impact
- UI can be confusing and hard to navigate
- Alert fatigue from too many alerts, especially non-business hours
- False positives
- Integration with GCP Dataform is needed
Monte Carlo pricing
The commentary is based on 14 reviews from Monte Carlo G2 reviews.
Monte Carlo's pricing model, based on the number of monitored tables, is a common concern. Some users find it difficult to estimate costs upfront and would prefer more granular control over table selection within schemas. Despite cost concerns, most users find the value provided justifies the expense.
Users sentiment
See the Monte Carlo pricing page.
Monte Carlo alternatives
MetaplaneBetter suited for software and IT companies. Has a free plan available. Growing faster than Monte Carlo. Users appreciate the proactive monitoring and seamless integrations, but dislike yaml configuration and occasional UI/UX issues. A strong Monte Carlo competitor and alternative.Read more
Data Quality MonitoringBetter fit for medium to large businesses. Has significantly more momentum. Specifically designed for finance, healthcare, and retail industries.Read more
iceDQBetter fit for medium to large enterprises, especially in finance and banking. Focuses on pre-production testing and ETL processes. Has more website traffic momentum as a Monte Carlo alternative and competitor.Read more
TableauBetter for business intelligence and visualization. Easier to use, with a drag-and-drop interface. Has broader industry applicability. A strong competitor and a Monte Carlo alternative for visualization needs. However, it is growing slower and has mixed reviews regarding pricing.Read more
Elastic StackBetter for visualizing relationships between data points. Geared towards developers and DevOps, particularly beneficial for log analysis and application monitoring. Has broader industry applicability but Monte Carlo may be a better data quality monitoring solution. Elastic Stack is growing faster.Read more
PantomathBetter suited for larger enterprises. Has stronger momentum in terms of web traffic and employee growth on LinkedIn. Focuses on finance, banking, insurance, and software/IT. Lacks user reviews currently. A Monte Carlo competitor and alternative.Read more
Monte Carlo FAQ
What is Monte Carlo and what does Monte Carlo do?
Monte Carlo is a data observability platform that uses machine learning to identify data downtime. It provides automated monitoring, alerting, and lineage tracing to help data teams maintain data reliability and trust. This helps prevent costly data incidents and ensures accurate, reliable data for business decisions.
How does Monte Carlo integrate with other tools?
Monte Carlo integrates with various data warehouses, data lakes, and ETL tools. It offers seamless integration with platforms like Snowflake, Databricks, and dbt, enabling comprehensive data observability across your data stack. It also integrates with Slack for notifications.
What the main competitors of Monte Carlo?
Top alternatives to Monte Carlo include Metaplane, iceDQ, and Anomalo, all offering data quality monitoring and anomaly detection. For broader data analysis and visualization, consider Tableau or Elastic Stack. Explo focuses on embeddable dashboards for customer-facing analytics.
Is Monte Carlo legit?
Yes, Monte Carlo is a legitimate data observability platform. It helps ensure data reliability with automated monitoring and alerting. It's highly rated by users for its out-of-the-box monitoring and excellent customer support. However, some users mention UI complexity and alert fatigue as potential drawbacks.
How much does Monte Carlo cost?
I couldn't find pricing details for Monte Carlo. Contact Monte Carlo directly to determine if it's worth the investment for your needs and budget. They may offer various plans and pricing options.
Is Monte Carlo customer service good?
Yes, Monte Carlo's customer service is highly regarded. Reviews consistently praise the support team's responsiveness, helpfulness, and proactive approach to addressing customer needs and implementing new features. They are seen as knowledgeable and dedicated to ensuring a positive customer experience.
Reviewed by
Michal has worked at startups for many years and writes about topics relating to software selection and IT management. As a former consultant for Bain, a business advisory company, he also knows how to understand needs of any business and find solutions to its problems.
Tymon is a seasoned CTO who loves finding the perfect tools for any task. He recently headed up the tech department at Batmaid, a well-known Swiss company, where he managed about 60 software purchases, including CX, HR, Payroll, Marketing automation and various developer tools.