> 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/viewing-data-quality-rules.md).

# Viewing Data Quality Rules

The Data Quality Rules page provides a centralized view of all Data Quality Rules configured in the application. Users can review rule details, monitor execution status, manage rule ownership, and analyze rule configurations from a single location.

![](/files/jyvjMyY5d4Z7l4Mk3hGI)

The Data Quality Rules page displays the following information for each rule:

<table data-search="false"><thead><tr><th width="188.5555419921875">Field</th><th>Description</th></tr></thead><tbody><tr><td>Rule Name</td><td>Displays the name of the Data Quality Rule. Selecting a rule opens its details page.</td></tr><tr><td>Purpose</td><td>Displays the business objective or reason for creating the rule.</td></tr><tr><td>Rule Creation Type</td><td>Indicates how the rule was created. Supported creation methods include Manual, Recommended, Load Metadata From Files, and OvalEdge API. Rules with the Recommended creation type are generated through the Rule Recommendations module.</td></tr><tr><td>Tags</td><td>Displays the tags associated with the rule. Tags help categorize and organize rules for easier discovery and management.</td></tr><tr><td>Status</td><td>Displays the current status of the rule, such as Active or Draft. Active rules can be executed and scheduled, while Draft rules remain available for configuration before activation.</td></tr><tr><td>Object Type</td><td>Displays the type of object associated with the rule, such as Table, Table Column, File, File Column, or Code.</td></tr><tr><td>Function</td><td>Displays the Data Quality Function used by the rule. The function defines the validation logic executed during rule execution. A help icon is available to view additional information about the selected function.</td></tr><tr><td>Dimension</td><td>Displays the Data Quality Dimension associated with the rule, such as Completeness, Accuracy, Validity, Consistency, Integrity, Timeliness, or Uniqueness.</td></tr><tr><td>Associated Objects</td><td>Displays the number of objects associated with the rule. Associated objects may include tables, columns, files, file columns, or code-based objects.</td></tr><tr><td>Steward</td><td>Displays the user responsible for monitoring and managing the rule.</td></tr><tr><td>Last Result</td><td>Displays the outcome of the most recent rule execution.</td></tr><tr><td>Last Run By</td><td>Displays the user who most recently executed the rule.</td></tr><tr><td>Last Run Date</td><td>Displays the date and time of the most recent execution.</td></tr><tr><td>Created By</td><td>Displays the user who created the rule.</td></tr><tr><td>Created Date</td><td>Displays the date and time when the rule was created.</td></tr><tr><td>Last Modified By</td><td>Displays the user who most recently updated the rule.</td></tr><tr><td>Last Modified On</td><td>Displays the date and time of the most recent modification.</td></tr></tbody></table>

**The following column-level actions are available on the Data Quality Rules page:**

<table><thead><tr><th width="113">Action</th><th>Columns</th></tr></thead><tbody><tr><td>Search</td><td>Rule Name, Purpose, Steward, Last Run By, Created By, Last Modified By</td></tr><tr><td>Filter</td><td>Rule Creation Type, Tags, Status, Object Type, Function, Dimension, Last Result</td></tr><tr><td>Sort</td><td>Associated Objects, Last Run Date, Created Date, Last Modified On</td></tr><tr><td>Help Icon</td><td>Function</td></tr></tbody></table>

The Function help icon provides additional information about the selected Data Quality Function. These capabilities help users efficiently locate, organize, and analyze Data Quality Rules.

### Configure Views

OvalEdge allows users to customize how data quality rule information is presented on the landing page through Configurable Views.&#x20;

<div data-with-frame="true"><figure><img src="https://lh7-rt.googleusercontent.com/docsz/AD_4nXcglcL94vRqQ_qNJMsVnAWhVFnG8CE8HfWjd-NpS0jVaMzYhOkTqLlxhsEvVMMxai5lx_K0icOZpy6XE1cxFYY-25Too0eWlMvtdi77EMvdWbII9c0gxznUSguBxxuOlRYkq7aeIA?key=3ghxFOjVM4opRqC6qDLp2028" alt=""><figcaption></figcaption></figure></div>

* **Column Management:**
  * **Adjust Columns:** Users can easily select, hide, or rearrange columns to focus on the data quality rule details most relevant to their needs.
* **Multiple Views:**
  * **Custom Views:** Users can define personalized views for various use cases. These custom views can be saved for quick access in the future.
  * **System-Defined Views:** OvalEdge also provides pre-built views optimized for common tasks, saving users time and effort.
* **Reset Functionality:**
  * **Restore Default View:** Users can easily revert to the default view configuration by clicking the Reset icon.

### User Actions

The Data Quality Rules provides actions that allow users to manage, organize, and execute Data Quality Rules efficiently. Users can perform these actions on one or more selected rules to streamline administration and monitoring activities.&#x20;

**Run Data Quality Rules:** The Run Data Quality Rules option allows users to execute one or more selected rules immediately. The system validates the associated objects using the configured function, input criteria, success criteria, and warning criteria, and records the execution results for review.

**Add Tags:** The Add Tags option allows users to associate one or more tags with selected Data Quality Rules. Tags help categorize rules based on business domains, projects, regulatory requirements, or other organizational classifications, improving searchability and rule management.

**Remove Tags:** The Remove Tags option allows users to remove existing tag associations from selected Data Quality Rules. This helps maintain accurate classification and ensures that rules remain aligned with current business and governance requirements.

**Delete Data Quality Rules:** The Delete Data Quality Rules option permanently removes the selected rules from the application. Users should verify that the rules are no longer required before performing this action.

{% hint style="info" %}
Only users with the required permissions can delete Data Quality Rules.
{% endhint %}

**Rules Summary:** The Rules Summary provides a centralized view of Data Quality Rule execution activities and upcoming scheduled executions. It enables users to monitor rule performance, review execution history, analyze object-level results, and track future rule runs from a single location.&#x20;

**Reset:** The Reset icon clears all applied search criteria, filters, sorting preferences, and selections on the Data Quality Rules page. This action restores the default view and allows users to start a new search or filtering operation without affecting any rule configurations.

## Rules Summary

The Rules Summary provides a consolidated view of Data Quality Rule execution activities and scheduled executions. It enables users to monitor rule performance, review execution outcomes, analyze object-level results, and track upcoming rule runs from a single location.

The Rules Summary contains the following tabs:

* **Rule Executions** – Displays the execution history and outcomes of Data Quality Rules.
* **Object Execution Results** – Provides detailed execution results for individual objects evaluated during rule execution.
* **Upcoming Executions** – Displays future scheduled Data Quality Rule executions and their planned run times.

### Rule Executions

The Rule Executions tab displays the execution history of Data Quality Rules across all supported object types, including Tables, Table Columns, Files, File Columns, and Codes.

<div align="left"><img src="/files/hbUFmXLCdyONM9vPzEE4" alt=""></div>

For each execution, users can review details such as:

* **Rule Name** – Name of the executed Data Quality Rule.
* **Object Type** – Type of object associated with the rule.
* **Rule Execution ID** – Unique identifier for the rule execution.
* **Result** – Overall execution outcome, such as Success, Warn, Failure, or Execution Failed.
* **Passed Objects** – Number of associated objects that satisfied the configured validation criteria.
* **Failed Objects** – Number of associated objects that did not meet the validation criteria.
* **Undetermined Objects** – Number of objects for which a result could not be determined.
* **Execution Failed Objects** – Number of objects that could not be processed due to execution-related issues.
* **Total Objects** – Total number of objects evaluated during execution.
* **Start Time** – Date and time when the execution started.
* **End Time** – Date and time when the execution completed.
* **Duration** – Total time taken to complete the execution.
* **Run By** – User who initiated the execution.

This information helps users monitor rule performance, identify execution failures, analyze validation outcomes across associated objects, and investigate data quality issues. The tab also provides filtering and sorting capabilities to quickly locate specific execution records.

### Object Execution Results

The Object Execution Results tab provides detailed execution results for each object evaluated during Data Quality Rule execution. It enables users to analyze validation outcomes at the object level and identify specific data assets affected by data quality issues.

<div align="left"><img src="/files/QwaTwuR1W5PFeGMM88Ur" alt=""></div>

For each execution result, users can review details such as:

* **Rule Name** – Name of the executed Data Quality Rule.
* **Object Type** – Type of object associated with the rule.
* **Rule Execution ID** – Unique identifier of the rule execution.
* **Object Execution ID** – Unique identifier of the object-level execution.
* **Connection Name** – Data source connection associated with the object.
* **Schema** – Schema or folder containing the object.
* **Object** – Name of the evaluated object.
* **Attribute** – Column or attribute associated with the validation.
* **Passed Row Count** – Number of rows that satisfied the configured validation criteria.
* **Failed Row Count** – Number of rows that did not satisfy the validation criteria.
* **Total Row Count** – Total number of rows evaluated during execution.
* **Result Value** – Value calculated during rule execution based on the selected Data Quality Function.
* **Result** – Execution outcome, such as Success, Warn, Failure, or Undetermined.
* **Run On** – Date and time when the execution was performed.

This information helps users investigate data quality issues, identify affected objects and attributes, review validation metrics, and support remediation activities. Filtering and sorting options are available to help users quickly locate specific execution results.

### Upcoming Executions

The Upcoming Executions tab displays the scheduled execution calendar for Data Quality Rules. It helps users review upcoming rule runs and verify that scheduling configurations are working as expected.

<div align="left"><img src="/files/s2YULpRgUUeZgaNBDQ1G" alt=""></div>

For each rule, users can view:

* **Rule Name** – Name of the Data Quality Rule.
* **Cron Entry** – Schedule expression used to determine the execution frequency and timing of the rule.
* **Execution Calendar** – A date-wise view showing the upcoming scheduled executions for the selected period.

The calendar displays a value for each date:

* 1 indicates that the rule is scheduled to run on that date.
* 0 indicates that no execution is scheduled for that date.

This view helps users quickly identify upcoming rule executions, validate schedule configurations, and understand the execution frequency of Data Quality Rules without navigating to the Jobs module.

{% hint style="info" %}
The scheduling information displayed in this tab is derived from the rule's configured schedule and reflects the upcoming planned executions.
{% endhint %}


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