Business Glossary

Various methodologies of building Business Glossary


A data governance business glossary is an essential data literacy tool and crucial for understanding the data in your organization and undertaking effective analytics. Without a business glossary, companies are often overwhelmed by the sheer number of conflicting terms and definitions used. When there is no standardization, organizations will encounter hurdles that impede critical business processes, across the board.

A business glossary enables users to find common terms and definitions, collaborate more easily on data assets, and move forward fluidly with data-driven growth initiatives. 

Business Glossary: A key tool for Data Literacy

Business glossary is a software application to store and manage all the business terms in standard format. Business glossaries have the following objectives: 

  1. Enable common understanding of the core business concepts and terminology *
  2. Improve the alignment between technology assets (with their technical naming conventions) and the business organization *
  3. A business glossary is not merely a list of terms and definitions. Each term will also be associated with other valuable Metadata: synonyms, metrics, lineage, business rules, the steward responsible for the term, etc. *
  4. Reduce the risk that data will be misused due to inconsistent understanding of the business* concepts 
  5. Maximize search capability and enable access to documented institutional knowledge *

Business Glossary is used for standardizing various business terms. Business Glossary terms goes through a well-defined governance approval process and can be used in stand alone without any data asset associated with it. There can be the same term with different definitions used in different lines of business (Domain).

Business Glossary Terms are at the KPI, or Column level. 

In OvalEdge, the business glossary term governs the entire metadata strategy. In general glossary terms are associated with a single DOMAIN that shows what kind of solution a specific industry delivers. Each domain will have multiple business units and subunits. The data collected in each domain may have PII/Confidential information that needs to be protected. Each business term will have some additional metadata content that needs to be listed for usage.

In OvalEdge we follow the following systematic approaches before creating a glossary term and associating the data objects to each term:

  1. Top Down Approach
  2. Bottoms Up Approach

Let us see these approaches in detail.

Top Down Approach

We can use this approach under following business use cases:

  • When BI department is new, companies want to use well-defined business terms so that they do not create bad practices.
  • When BI department is established, there is not much confusion about the business terms.
  • When companies want to adapt to the standard definitions anyhow.
  • When your industry is well regulated, and terms are well defined by the regulation or industry best practices. For example in the financial industry lots of KPIs are well defined and understood. 

This methodology is divided into five sections as shown in below figure:

Bottoms Up Approach

We can use this approach under following business use cases:

  • When BI Department is in place and business terms have a lot of confusion.
  • The data-warehouse is in place and most of the terms are well defined and standard.
  • When your industry is scattered and not many standards are in place for KPIs. For example, in the health-care industry, not many KPIs are standard; they are not even organization specific. 

This methodology is divided into five sections as shown in below figure:

Where to Start?

Before you start the data literacy implementation, start with the following steps.

  1. Reach out to subject matter experts in order to define the process.
    1. Get the proper terms and definitions.
    2.  In this process, you also discuss the Organization hierarchical structure and Configure Domains/Categories/Subcategories that will contain the term. 
    3. Identify all the data that has to be protected and classify them as PII information. 
    4. Assign a designated “Steward” and “Reviewer” on each Domain and/or Category(optional). They can manage the business metadata, enrich the term definitions, and manage the associations to the technical metadata.
  2. Multiple business units contribute to the definition as well.
  3. If there is a mismatch the committee has to go back and forth to agree on final definitions and usage of these definitions. (Consensus-General Agreement)
  4. See if there are any additional terms needed to be created and defined.
    Related terms: always the best practice to capture all the associated terms to the data, which will help in better impact analysis/data analysis. Terms you have as a related term is always either any of the following:
    1. Synonym of the existing term
    2. Is calculated from another term
    3. Inherited from another term
    4. Logically related to another term 
  5. Approve and publish the term/ terms.
  6. Revisit the term definitions periodically to avoid the business glossary becoming obsolete upon completion since no one in the business will actually utilize this information for compliance with any new regulations.

Glossary terms provide a direct link to the data objects like databases, tables, columns, files, reports, and queries. OvalEdge uses the glossary of terms to organize data objects functionally. You can run algorithms on the glossary terms to recommend other related data objects to be connected and explored. See this article AI to build Business Glossary to know more on how to use AI algorithms to build the Business Glossary.