Description
Anomalo is an automated data quality monitoring platform that uses machine learning to detect and diagnose data issues before they impact business decisions. The platform continuously monitors data assets for anomalies, schema changes, distribution shifts, and other quality issues without requiring manual rule configuration. By automatically establishing baselines and adapting to evolving data patterns, Anomalo provides comprehensive data quality assurance with minimal setup and maintenance. The platform's focus on proactive data health monitoring enables organizations to build trust in their data and prevent costly decisions based on flawed information.
Key Features
- Automated anomaly detection
- ML-powered baseline modeling
- Root cause analysis
- Schema and metadata monitoring
- Data quality alerting
Use Cases
- Enterprise data quality assurance
- Data pipeline monitoring
- Analytics reliability
- Regulatory compliance
- Data governance implementation
Pricing Model
Volume-based enterprise subscription
Integrations
Data warehouses, Business intelligence platforms, Data pipelines, Alerting systems, Workflow tools
Target Audience
Data engineers, Data governance teams, Analytics leaders, Data reliability engineers, Business intelligence developers
Launch Date
2018
Available On
Cloud-based platform, Data warehouse integration, Enterprise deployment
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