Integration

Use with Business Glossary

In the Business Glossary, the Recommendations section displays recommended data objects related to the term.

Terms with Recommendations:

• Users can view recommended data objects for terms.

• Users can accept or reject these suggestions.

• A filter allows users to view recommendations from a specific model (the default shows all models).

Terms without Recommendations:

• If a term lacks recommendations, the section displays "No Recommendations Found. Click Here to configure an AI model to generate recommendations."

• Clicking this message directs users to the Data Classification Recommendation landing page. Here, users can choose to create a new AI model. Opting to proceed opens the "Create Model Stepper" pop-up pre-populated with data based on the viewed term.

Configure Regex

Users can configure AI Recommendation Settings directly from a Term Summary page using the 9-dots menu.

These settings define custom regex patterns and associated boost values to improve recommendation precision for specific terms.

Field Name	Description
Objects Name Matching Regex	Enter a regular expression pattern to match against object names. When an object’s name matches this regex, it receives an additional Smart Score boost as defined below. Example: `(?i)email
Objects Data Matching Regex	Enter a regular expression pattern to match against object data values. When an object’s data matches this pattern, it receives a data-level Smart Score boost. Example: [A-Za-z0-9._%+-]+@[A-Za-z0-9.-]+\.[A-Za-z]{2,} — detects email-like data patterns.
Boost Score on Name Regex Match By	Specify the number of Smart Score points to increase when an object name matches the configured name regex. Example: Setting this to 10 adds +10 to the Smart Score for each matching object.
Boost Score on Data Regex Match By	Specify the number of Smart Score points to increase when an object’s data matches the configured data regex. Example: Setting this to 15 adds +15 to the Smart Score for each object whose data matches the regex.

Recommendation Keywords

Users can configure keywords and synonyms for the term. This will help with AI recommendations.

The data object that matches the term name and the synonym or configured keyword is recommended.

Example: The Term “Customer” is curated in the Business Glossary. Stakeholders can configure AI recommendation Keywords for this term, like Client, Customer_name, prospectus, etc, to get recommendations for the data object matching these keywords.

Automate AI Models with Job Workflow

Users can schedule a model through Job Workflow. This allows users to schedule the AI model to run after a connector is crawled. If the connector has newly crawled data, the AI model will execute automatically and generate recommendations for newly crawled objects, ensuring they always work with the most up-to-date data.

View Results in Object Summary

The Object Summary section in the Data Catalog allows users to view, accept, or reject AI-generated term recommendations. These recommendations are derived from the Data Classification Recommendation (DCR) AI models.

Users can accept or reject term recommendations directly within the Object Summary without navigating to the DCR module.

A simple accept (✔) or reject (✖) action allows users to validate term associations with minimal effort.

When a user accepts a term recommendation, it is immediately associated with the corresponding data object within the system.

If multiple term recommendations exist for the same data object, they are all displayed within the Object Summary.

Users can assess each recommendation separately, selecting the most relevant term(s) for accurate classification.