Browse Prior Art Database

Cognitive suggestion of Business Glossary match with Information Assets

IP.com Disclosure Number: IPCOM000250586D
Publication Date: 2017-Aug-04
Document File: 3 page(s) / 68K

Publishing Venue

The IP.com Prior Art Database

This text was extracted from a PDF file.
This is the abbreviated version, containing approximately 55% of the total text.

Nowadays Data Governance has become very important in every company data infrastructure. In

the center of Data Governance systems, there is Business Glossary, holding business terms

which might be then related to certain Information Assets. Such fitting is allowing easier

recognition of content or purpose of Information Asset. When usage of such prepared

environment is usually easy and convenient, creation of those associations is long and heavy

process.

We are proposing cognitive solution that will learn best matches of Information Assets and

Business Glossary terms based on already created environments.

First we need to make some definitions of Business Glossary Assets and Information Assets, so

further usage of those terms is fully understood.

In Business Glossary (which might be some database with user interface), there are stored

Business Glossary Assets (BGA). Such Assets might be:

- Categories - Terms - Governance Rules - Governance Policies

Each of those are words or sentences that are describing business of the company.

For example:

- Categories: Documents, Invoices - Terms: Customer Name, Customer Address, Invoice Number - Governance Policy: Ensure Invoice Correctness - Governance Rules: Check correctness of Customer Address, Check correctness of

Invoice Number

Terms can be divided into Categories and Rules into Policies. So in our example We can have

following tree of Terms:

Documents -> Invoices -> Customer Name, Customer Address, Invoice Number

Ensure Invoice Correctness -> Check correctness of Customer Address, Check correctness of

Invoice Number

Informatio...