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29 docs tagged with "data quality"

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Anomalo

Integrate, catalog, and govern Anomalo assets in Atlan.

Ataccama

Integrate, catalog, and govern Ataccama assets in Atlan.

Compute and cost tracking

Understand how Data Quality Studio uses compute resources, how costs are calculated, and practical ways to track and optimize spend for Snowflake and Databricks.

Configure alerts

Set up real-time notifications for data quality rule failures via Slack or Microsoft Teams.

Contracts

Learn how to manage data contracts and agreements in Atlan to ensure data quality and compliance.

Data Quality Studio

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

Monte Carlo

Integrate, catalog, and govern Monte Carlo assets in Atlan.

Most recent day scans

Understand how limiting rules to the most recent day of data improves monitoring results in Atlan.

Notification routing

Understand how data quality alerts are routed to different channels based on asset scope and priority settings

Operations

Atlan crawls and manages the following data quality operations and results from Snowflake.

Qualytics

Integrate, catalog, and govern Qualytics assets in Atlan.

Roles and permissions

Explanation of Snowflake's security model and role requirements for data quality operations.

Rules and dimensions

Reference for available data quality rules and classification dimensions in Snowflake data quality.

Set up Databricks

Configure Databricks to enable data quality monitoring through Atlan.

Set up Snowflake

Configure Snowflake to enable data quality monitoring through Atlan.

Soda

Integrate, catalog, and govern Soda assets in Atlan.

Use AI-suggested rules

Let Atlan suggest data quality rules automatically based on your asset's metadata structure, and apply them in a few clicks.

What's auto reattachment

Understand automatic reattachment of data quality rules to assets that are dropped and recreated.

What's Data Quality Studio

Understand Atlan's Data Quality Studio and how it enables business and data teams to collaborate on defining, monitoring, and enforcing data quality expectations