Enable Metadata Enrichment AI to Generate Data Quality Rules

Administrators and data governance users need the ability for metadata enrichment AI to automatically suggest or create data quality rules based on discovered metadata, profiling results, business terms, data classes, and observed data patterns.

Currently, metadata enrichment can help identify and classify metadata, such as data classes, business terms, descriptions, and profiling insights. However, users also need a way to convert those insights into actionable data quality rules without having to manually define each rule from scratch.

The requested enhancement is to add AI-assisted data quality rule generation as part of the metadata enrichment workflow. After metadata enrichment is completed, the system should be able to recommend relevant data quality rules based on the enriched metadata and profiling results.

Examples of recommended rules could include:

• Completeness rules for fields that should not be null

• Valid value rules based on detected patterns or reference values

• Format rules for fields such as email addresses, phone numbers, dates, or identifiers

• Uniqueness rules for likely primary key or identifier columns

• Range rules for numeric or date fields

• Consistency rules between related fields

• Rules based on assigned business terms or data classes

• Rules based on historical profiling results or observed anomalies

Ideally, the feature should allow users to review, edit, approve, and publish AI-generated data quality rules before they are activated. The AI should provide an explanation for why each rule was recommended, including the metadata, profile statistics, business term, data class, or pattern that influenced the recommendation.

The enhancement should also support creating rules in draft mode so data stewards or governance users can validate them before deployment. Users should be able to select individual recommendations, bulk-create rules, and track which rules were generated from metadata enrichment.

This capability would reduce manual effort, accelerate data quality implementation, improve consistency across governed assets, and help organizations convert metadata insights into operational data quality controls more efficiently.