> For the complete documentation index, see [llms.txt](https://docs.ovaledge.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.ovaledge.com/release8.2/data-quality/data-quality-rules.md).

# Data Quality Rules

Data Quality Rules help organizations monitor, validate, and maintain the quality of data across various data assets. By applying predefined or custom validation logic, users can identify data quality issues, enforce business standards, and improve confidence in data used for reporting, analytics, governance, and operational processes.

Each Data Quality Rule uses a **Data Quality Function** to evaluate data against specific conditions. Functions define the validation logic used to assess data quality attributes such as completeness, accuracy, validity, uniqueness, consistency, integrity, and timeliness.

OvalEdge provides a library of system-defined **Data Quality Functions** that support common validation scenarios. Organizations can also create and manage custom Data Quality Functions through the Data Quality Functions module to address business-specific validation requirements. These functions can then be associated with Data Quality Rules and applied across multiple data assets.

By combining reusable Data Quality Functions with configurable Data Quality Rules, organizations can establish standardized data quality controls, automate validation processes, and proactively identify and remediate data quality issues.


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