Data Quality Studio
Atlan runs data quality natively in your warehouse—automated checks, alerts, and governance workflows that execute where the data lives.
With native integration to BigQuery, Databricks, and Snowflake, you can leverage platform-specific data quality functions and create rules that automatically validate your data assets. The studio helps you identify data quality issues early, track quality trends over time, and maintain compliance with your data governance policies.
Core offerings
Platform integration
Set up data quality monitoring for BigQuery, Databricks, and Snowflake environments with native platform capabilities
Automated monitoring
Enable continuous data quality checks and validation with real-time rule execution and metrics tracking
Alert management
Configure notifications for data quality issues with customizable routing and escalation workflows
Auto-re-attachment
Automatically re-attach quality rules after schema changes to maintain continuous monitoring
Get started
Follow this process to set up and configure data quality monitoring in your environment.
Choose your platform
Select BigQuery, Databricks, or Snowflake and follow the platform-specific setup guide to configure authentication and initial settings.
Enable data quality
Configure the connection and enable data quality monitoring with platform-specific credentials and settings.
Configure alerts
Set up notifications for data quality issues and rule failures to maintain continuous monitoring.
Platform-specific features: Snowflake includes auto-re-attachment capabilities and migration tools, Databricks offers serverless compute integration, and BigQuery leverages stored procedures for rule execution. Choose the platform that best fits your data infrastructure.