Soda

Soda is an AI-native, fully automated data quality platform designed to help teams continuously monitor, detect, and resolve data issues across their modern data stack. It connects to data warehouses, lakes, and databases to automatically profile datasets, identify anomalies, and surface potential quality problems such as missing values, schema changes, outliers, or inconsistent records. Using AI-driven rules and recommendations, Soda enables users to define and maintain data quality checks without extensive SQL or manual configuration, making it accessible to both data engineers and business stakeholders.

The platform supports table-level and record-level analysis, allowing users to quickly drill down from high-level data health metrics to specific problematic rows. Soda also provides alerting and collaboration features so teams can triage incidents, assign ownership, and track resolution directly within their existing workflows. Common use cases include monitoring data pipelines in production, validating data for analytics and BI dashboards, ensuring reliability for machine learning models, and enforcing data quality standards for regulatory or operational reporting. By automating detection and providing clear, actionable insights, Soda helps organizations reduce time spent troubleshooting data issues, increase trust in their data assets, and maintain reliable, high-quality data at scale.