Add DQ Rules to Terms

Linking DQ evaluation rules to terms in your glossary enables automatic, consistent data quality checks across your entire data landscape. When a term is detected on or assigned to an attribute, all associated DQ rules are applied automatically during evaluation.

Why add DQ rules to terms?

Adding DQ rules to terms connects your business vocabulary directly to data quality validation. This approach offers several advantages over applying rules individually to attributes:

Scalability: Define quality standards once on a term and have them applied everywhere that term appears. A single Email term with validation rules can enforce consistent checks across hundreds of attributes in different data sources.
Consistency: Every attribute tagged with a term receives identical validation logic. This eliminates inconsistencies that arise when different teams create separate rules for the same data types.
Governance alignment: Quality standards are documented alongside business definitions, creating a single source of truth. When requirements change, updating a term’s rules propagates changes everywhere that term is used.
Reduced maintenance: Instead of managing rules on thousands of individual attributes, maintain them centrally on a manageable set of terms.

For DQ rules to be applied through terms, the terms must first be assigned to attributes—either through term detection or manual assignment. See detect-terms.adoc for more information.

Prerequisites

Before adding DQ rules to a term, ensure you have:

Created the DQ evaluation rules you want to apply. See DQ Rules.
Created or identified the term you want to configure. See create-term.adoc.

Add a DQ rule to a term

To add a DQ rule to a term:

Go to Glossary > Terms.
Select the term type (for example, Business terms) and open the term you want to configure.
Select the DQ settings tab.
In the Data Quality Evaluation section, find the dimension where you want to add a rule (for example, Validity, Completeness, or Accuracy) and select Add Rule.

Any custom dimensions configured in your environment also appear here alongside the default dimensions.
Select the rule from the list and then select Apply.
Repeat for any additional rules you want to add across different dimensions.
To enable automatic evaluation on all attributes where this term is detected, select Apply the following rules automatically on all attributes with this term.
Publish your changes to make the configuration active.

Automatic rule application

When Apply the following rules automatically on all attributes with this term is enabled, the system applies the term’s DQ rules during evaluation without requiring manual rule assignment on each attribute.

This means:

When term detection assigns this term to an attribute, the DQ rules become active on that attribute.
When you run DQ evaluation on a catalog item, all term-linked rules are included automatically.
Results are aggregated by dimension and contribute to the overall quality score.

If this option is disabled, the rules remain associated with the term but are not automatically applied during evaluation. You would need to apply rules directly to attributes instead.

View rules applied to a term

To review which DQ rules are currently mapped to a term:

Go to Glossary > Terms.
Open the term and select the DQ settings tab.

Rules are displayed under their respective dimension categories. You can remove a rule by selecting the delete icon next to it.

Example: Configuring DQ rules for an Email term

This example shows you how to configure a business term with DQ rules that validate email data consistently across your organization.

Scenario

Your organization stores customer email addresses in multiple systems: a CRM, a marketing platform, and a data warehouse. You want to ensure that all email data meets the same quality standards, regardless of where it resides.

Solution

Add DQ rules to a single Email term to define your quality standards once. When term detection identifies email attributes across your data sources, the rules apply automatically during DQ evaluation.

Configuration

For an Email term, consider adding rules across multiple dimensions:

Dimension Rule purpose Example logic

Dimension	Rule purpose	Example logic
Validity	Check that values follow a valid email format	Value matches pattern `[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}`
Completeness	Ensure email fields are not empty where required	Value is not null or empty string
Uniqueness	Detect duplicate email addresses that could indicate data quality issues	No duplicate values within the dataset

Validity

Check that values follow a valid email format

Value matches pattern [a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}

Completeness

Ensure email fields are not empty where required

Value is not null or empty string

Uniqueness

Detect duplicate email addresses that could indicate data quality issues

No duplicate values within the dataset

Result

Once you configure and publish the term:

Term detection identifies attributes containing email data across all your connected sources.
The Email term is assigned to matching attributes.
When you run DQ evaluation, all three rules apply automatically.
Results show you quality scores broken down by dimension, helping you identify whether issues stem from formatting problems, missing data, or duplicates.

If you later decide to tighten email validation (for example, blocking disposable email domains), update the rule on the term once and the change applies everywhere.

Next steps

Run DQ evaluation to apply your configured rules.
Run term detection to assign terms to attributes across your catalog.
Add DQ rules directly to attributes for targeted validation outside term-based governance.

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