Metaplane provides a data observability platform that features automated anomaly detection, end-to-end column-level lineage, and real-time schema change alerts to ensure data integrity across business operations. By enabling data teams to proactively identify and resolve data quality issues, Metaplane helps prevent disruptions that could impact critical business metrics.
Funding
$22.2M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
GR+1Founders
Product
Problem
Data teams often struggle to maintain data integrity across complex data pipelines, leading to inaccurate business insights and operational disruptions. Identifying and resolving data quality issues proactively is challenging due to the lack of visibility into data lineage, schema changes, and anomalies. Traditional methods of data monitoring require manual configuration and coding, which is time-consuming and difficult to scale.
Solution
Metaplane provides an automated data observability platform that enables data teams to proactively monitor and resolve data quality issues. The platform features end-to-end column-level lineage, automated anomaly detection, and real-time schema change alerts, providing comprehensive visibility into the data pipeline. By automatically detecting data anomalies and providing clear lineage information, Metaplane helps data teams quickly identify the root cause of data quality issues and prevent disruptions to critical business metrics. The platform integrates seamlessly with existing data infrastructure, allowing teams to implement data observability without extensive manual configuration.
Target Audience
Metaplane is designed for data engineers, data analysts, and data scientists who are responsible for maintaining data quality and ensuring the reliability of data-driven insights.
Features
- Automated anomaly detection using machine learning to identify unexpected changes in data patterns
- End-to-end column-level lineage visualization to trace data flow from source to consumption
- Real-time schema change alerts to notify teams of modifications to data structures
- Data quality monitoring with customizable metrics and thresholds
- Pipeline monitoring to track the duration and status of data pipelines
- PR merge testing to prevent data quality issues during code deployments
- Data insights to optimize data usage and reduce data debt
- Integrations with popular data platforms, including Snowflake, BigQuery, and Databricks