Skip to main content

Data Quality Studio ➕ Available via the Data Quality Studio package

Data Quality Studio provides comprehensive data quality monitoring and governance capabilities across your data sources. Monitor data quality metrics, set up automated quality checks, configure real-time alerts, and establish governance workflows to maintain high data standards throughout your organization.

With native integration to 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 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.

1

Choose your platform

Select Databricks or Snowflake and follow the platform-specific setup guide to configure authentication and initial settings.

2

Enable data quality

Configure the connection and enable data quality monitoring with platform-specific credentials and settings.

3

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, while Databricks offers serverless compute integration. Choose the platform that best fits your data infrastructure.