Bigeye is designed by former data engineers and data scientists to provide a single place for engineers, analysts, data producers, and data consumers to work together on data quality for their organization. Bigeye makes essential tools for addressing data quality like table health, data quality SLAs, alerts, and new monitoring configuration accessible to anyone in the organization. Bigeye also offers custom metric definitions, customizable thresholds, full API access, an Airflow operator, webhooks, and other features engineers need to get the most value from a monitoring and alerting system.
Data teams can start using Bigeye without installing invasive daemons in their infrastructure or adding new dependencies to their data modeling workflow. Bigeye trains its anomaly detection models and begins detecting issues in minutes to hours with little impact on the data warehouse. Bigeye’s metric collection framework is heavily optimized to take advantage of data warehouse performance characteristics and to reduce the load incurred even when collecting thousands of data quality metrics.
