# Data Quality Studio

> Part of Govern data

Monitor and maintain data quality across your data sources with automated quality checks, alerts, and governance workflows

- [BigQuery Data Quality Studio](https://docs.atlan.com/llms/governance/data-quality/bigquery/llms.txt): Set up and configure BigQuery for data quality monitoring through Atlan.
- [Set up BigQuery](https://docs.atlan.com/llms/governance/data-quality/set-up-bigquery/llms.txt): Configure BigQuery to enable data quality monitoring through Atlan.
- [Enable data quality on connection](https://docs.atlan.com/llms/governance/data-quality/bigquery-how-tos-enable-data-quality/llms.txt): Enable and configure data quality for your BigQuery connection in Atlan.
- [Databricks Data Quality Studio](https://docs.atlan.com/llms/governance/data-quality/databricks/llms.txt): Set up and configure Databricks for data quality monitoring through Atlan.
- [Set up Databricks](https://docs.atlan.com/llms/governance/data-quality/set-up-databricks/llms.txt): Configure Databricks to enable data quality monitoring through Atlan.
- [Enable data quality on connection](https://docs.atlan.com/llms/governance/data-quality/databricks-how-tos-enable-data-quality/llms.txt): Enable and configure data quality for your Databricks connection in Atlan.
- [Snowflake Data Quality Studio](https://docs.atlan.com/llms/governance/data-quality/snowflake/llms.txt): Set up and configure Snowflake for data quality monitoring through Atlan.
- [Set up Snowflake](https://docs.atlan.com/llms/governance/data-quality/set-up-snowflake/llms.txt): Configure Snowflake to enable data quality monitoring through Atlan.
- [Enable data quality on connection](https://docs.atlan.com/llms/governance/data-quality/snowflake-how-tos-enable-data-quality/llms.txt): Enable and configure data quality for your Snowflake connection in Atlan.
- [Upgrade Snowflake Data Quality Studio](https://docs.atlan.com/llms/governance/data-quality/upgrade-snowflake/llms.txt): Upgrade your Snowflake data quality setup to the latest version
- [Enable anomaly detection](https://docs.atlan.com/llms/governance/data-quality/enable-anomaly-detection/llms.txt): Enable ML-based anomaly detection on a Snowflake table to automatically monitor row count and freshness without manual thresholds.
- [Configure alerts](https://docs.atlan.com/llms/governance/data-quality/configure-alerts/llms.txt): Set up real-time notifications for data quality rule failures via Slack, Microsoft Teams, Jira, or ServiceNow.
- [Configure webhooks](https://docs.atlan.com/llms/governance/data-quality/configure-webhooks/llms.txt): Send data quality rule lifecycle and result events to external systems using webhooks.
- [Enable most recent day scanning](https://docs.atlan.com/llms/governance/data-quality/enable-most-recent-day-scanning/llms.txt): Configure data quality rules to scan only the most recent day's data for faster, more efficient monitoring.
- [Query failed rows](https://docs.atlan.com/llms/governance/data-quality/query-failed-rows/llms.txt): View and export the actual data rows that failed data quality rules to investigate and resolve data quality issues.
- [Enable query failed rows](https://docs.atlan.com/llms/governance/data-quality/enable-query-failed-rows/llms.txt): Enable the query failed rows feature in Labs so users can investigate data quality issues by viewing the actual rows that failed DQ rules.
- [Configure connection for failed rows](https://docs.atlan.com/llms/governance/data-quality/configure-connection-for-failed-rows/llms.txt): Configure BYOC credentials and query settings on your BigQuery, Databricks, or Snowflake connection to enable failed rows queries.
- [Use AI-suggested rules](https://docs.atlan.com/llms/governance/data-quality/use-ai-suggested-rules/llms.txt): Let Atlan suggest data quality rules automatically based on your asset's metadata structure, and apply them in a few clicks.
- [Run rules on demand](https://docs.atlan.com/llms/governance/data-quality/run-rules-on-demand/llms.txt): Trigger data quality rules immediately at the table or rule level without waiting for the next scheduled run. Supported for Snowflake and Databricks.
- [What's Data Quality Studio](https://docs.atlan.com/llms/governance/data-quality/data-quality-studio/llms.txt): Understand Atlan's Data Quality Studio and how it enables business and data teams to collaborate on defining, monitoring, and enforcing data quality expectations
- [What's anomaly detection](https://docs.atlan.com/llms/governance/data-quality/anomaly-detection/llms.txt): Understand how Atlan uses Snowflake's native ML-based anomaly detection to automatically monitor row count and freshness without manual thresholds.
- [What's auto reattachment](https://docs.atlan.com/llms/governance/data-quality/auto-re-attachment-rules/llms.txt): Understand automatic reattachment of data quality rules to assets that are dropped and recreated.
- [Most recent day scans](https://docs.atlan.com/llms/governance/data-quality/most-recent-day-scans/llms.txt): Understand how limiting rules to the most recent day of data improves monitoring results in Atlan.
- [Notification routing](https://docs.atlan.com/llms/governance/data-quality/notification-routing/llms.txt): Understand how data quality alerts are routed to different channels based on asset scope and priority settings
- [Compute and cost tracking](https://docs.atlan.com/llms/governance/data-quality/compute-and-cost-tracking/llms.txt): Understand how Data Quality Studio uses compute resources, how costs are calculated, and practical ways to track and optimize spend for Snowflake, Databricks, and BigQuery.
- [Data quality permissions](https://docs.atlan.com/llms/governance/data-quality/data-quality-permissions/llms.txt): Reference for data quality permission scopes and configuration in Atlan.
- [Operations](https://docs.atlan.com/llms/governance/data-quality/operations/llms.txt): Atlan crawls and manages the following data quality operations and results from Snowflake.
- [Rules and dimensions](https://docs.atlan.com/llms/governance/data-quality/data-quality-rules/llms.txt): Reference for available data quality rules and classification dimensions in Snowflake data quality.
- [Run on the most recent day of data](https://docs.atlan.com/llms/governance/data-quality/run-on-most-recent-day/llms.txt): Reference for restricting data quality rules to only the most recent day's data.
- [Rule types and failed rows validations](https://docs.atlan.com/llms/governance/data-quality/rule-types-and-failed-rows/llms.txt): Reference of Data Quality Studio rule types, restrictions, and how failed rows validation works
- [Anomaly detection results](https://docs.atlan.com/llms/governance/data-quality/anomaly-detection-results/llms.txt): Reference for anomaly detection result fields, status values, and how results flow from Snowflake to Atlan.
- [Data Quality Studio setup reference (Snowflake)](https://docs.atlan.com/llms/governance/data-quality/dq-studio-snowflake-setup/llms.txt): The Snowflake-side setup facts for Data Quality Studio—roles, grants, the ATLAN_DQ database, warehouse scope, scheduling constraints, execution model, and connector coverage status.
- [Webhook payload](https://docs.atlan.com/llms/governance/data-quality/webhook-payload-reference/llms.txt): Event types, payload structure, and field definitions for data quality webhook events.
- [Failed rows connection](https://docs.atlan.com/llms/governance/data-quality/troubleshooting-failed-rows-connection/llms.txt): Troubleshoot issues with configuring connections for failed rows queries, including connection status, query button visibility, and query execution failures.
- [Snowflake rules on views with non-deterministic functions](https://docs.atlan.com/llms/governance/data-quality/troubleshooting-snowflake-non-deterministic-views/llms.txt): Troubleshoot Snowflake data quality rule creation failures caused by non-deterministic functions inside view definitions, with recommended workarounds.
- [Failed rows](https://docs.atlan.com/llms/governance/data-quality/failed-rows-faq/llms.txt): Frequently asked questions about querying failed rows, including nudge banner behavior and configuration requirements.
- [Roles and permissions](https://docs.atlan.com/llms/governance/data-quality/roles-and-permissions/llms.txt): Explanation of Snowflake's security model and role requirements for data quality operations.
- [Setup and configuration](https://docs.atlan.com/llms/governance/data-quality/setup-and-configuration/llms.txt): Common questions about Databricks data quality setup and configuration.
- [Manage data quality rules](https://docs.atlan.com/llms/governance/data-quality/manage-dq-rules/llms.txt): Create, update, retrieve, and delete data quality rules programmatically using the Atlan Python SDK (pyatlan). Use DataQualityRule to manage DQ rules and monitors via the SDK.
- [Plan and run data quality monitoring](https://docs.atlan.com/llms/governance/data-quality/plan-and-run-data-quality/llms.txt): How to scope data quality to the assets that matter, choose and sequence rules, route alerts without creating noise, and position monitoring against pipeline tests.