Metaplane

ML-based monitoring in Metaplane uses machine learning models to analyze historical data. It detects anomalies and data quality issues automatically. This proactive approach minimises manual intervention and ensures reliable data.

Schema change alerts notify users instantly when there’s a change in the data schema. This helps maintain data integrity. It ensures that any unexpected changes are quickly identified and addressed.

Yes, Metaplane offers seamless integration. It connects with major data sources smoothly. This helps in consolidating data monitoring across platforms.

Metaplane detects data drift by comparing current data with historical data. It identifies inconsistencies and deviations automatically. Alerts are triggered for the data team to investigate and resolve.

Lineage impact analysis provides insights on how data changes affect downstream processes. This helps in understanding dependencies. It ensures that data adjustments don’t negatively impact other areas.

Metaplane offers intuitive and user-friendly dashboards. These dashboards provide real-time visual representation of data quality. They help in easily identifying and addressing data issues.

Yes, Metaplane boasts a user-friendly interface. It is designed for both technical and non-technical users. This ensures ease of use and quick adoption.

Metaplane is highly scalable and suits various team sizes. It accommodates small teams as well as large enterprises. This flexibility makes it ideal for different organizational needs.

Metaplane can send alerts for various events. These include schema changes, data quality issues, and job performance. Alerts can be customized based on user preferences.