Enterprises continue to grow and so does data environment complexity, including data terminology both internal and external to a particular enterprise. Consider a firm that builds computer chips for new devices. Each project may have its own Database System and Data Dictionary. Yet engineers, management, accountants, and customers need to speak the same language to understand one another. A Data or Business Glossary solves this complexity, by referencing vocabulary needed to run the company. A Business Glossary covers  multiple Data Dictionaries and business segments.

The Business Glossary enhances Data Governance, through an organized list of terms, with specific meanings. The Business Glossary has been discussed by many different organizations from a DAMA International Webinar to resources looking to help mitigate Data Governance Problems.

What is a Business Glossary?

 A Business Glossary defines terms across a business domain, providing an authoritative source for all business operations, including its Database Systems. Although the term “Business Glossary” and “Data Dictionary” may be used interchangeably, they have different meanings.  Take the Linked Data Glossary, created by the W3C (World Wide Web Consortium). This Business Glossary helps IT managers, Web developers and the everyday visitor understand “publishing structured data using Linked Data Principles.

The National Center for Health Statistics (NCHS) and U.S. Department of Housing and Urban Development (HUD) have created a Linked Data Data Dictionary towards understanding the health and well-being of people living in HUD-assisted housing, by using data connected by both agencies. Thus, the W3C Linked Data Glossary can be used towards the NCHS-HUD business success integrating housing and health data by its common terminology.

As mentioned in a recent Demystifying Data Dictionary article The International Standards Organization (ISO) proposes a model for the financial industry, in Understanding the Data Dictionary.  This model includes a business Metadata layer, as described by Zaino, in Metadata and Data Governance Success: The Three-Level Approach as the “definitions for the physical data that people will access in business terms.” But IT managers and people in finance need to understand this language in a Data Dictionary. The consulting of a Business Glossary, such as the Investor Glossary from the US Securities and Exchange Commission, would help understand and communicate investment terminology comprising the messages and business data elements in different database systems. This Business Glossary, in addition to a Data Dictionary, increases Big Data’s value, reducing miscommunication about what reports, generated from any Database System, related to the business, mean.

Advantages of a Business Glossary

• Allows the Business to Own Terms and Meaning: Typically, clients will have a need, such as creating a medical device for patients to communicate vital measurements to clinicians. IT engineers will create an application, including a database or databases to address the desire, which would include a Data Dictionary of the database System. IT may create data elements where a patient can record blood pressure, sending it to the clinician. However, the clinician would probably not be interested in every patient’s blood pressure measurements. How will IT engineers know which values would interest a clinician? Using a Business Glossary, such as the one created by Harvard Medical School, an optimal blood pressure measurement would be defined as 120/80 mm HG or below. IT tailors the application to flag measurements above 120/80 mm HG. By creating a database system in compliance with Business Definitions (e.g. for blood pressure), data becomes more meaningful to business stakeholders not just IT.

• Highlights How Vocabulary may Differ across Business Functions: Different business stakeholders define common words differently. For example, take the word “invoice.” An “invoice,” from the perspective of a consumer, may refer to the document sent that requests payment. In the IT engineer’s eyes an invoice may mean the process of creating a bill. In accounting, “invoice” may refer to the document sent to request payment of a customer. Clarification of whether an invoice data element is a physical item or a process becomes necessary when generating invoice reports. The University of California, San Francisco (UCSF) defines invoice, in its research business, as a “statement of amount due on the billing terms” . Should IT, at UCSF, need to create a database system that processes payments, the UCSF glossary provides structure in defining an “Invoice Data” element.

• Ensures more Trust in Data across the Business: Nothing can be more frustrating than finding out, towards the release of an application, that IT’s conception of the business need does not match what the stakeholders meant. The employees across the business think that Information Technology has not listened to them. IT may think that its clients have not communicated what was needed at the start of the database project. Having a Business Glossary, where the semantic differences in the business have been clarified, provides an excellent tool to keep everyone on the same page, when creating database systems, an application, or in updating a Data Dictionary. As IBM highlights, its Infosphere Business Glossary “improves Data Governance Programs by helping to deliver trusted information.” IBM provides an example of a Business Glossary tool to ensure business alignment across an enterprise.

Alternatives to a Business Glossary

Data or Business Glossaries do have some draw backs. First, a Business Glossary adds unneeded complexity. For example, a start-up organization of fewer 20 people may not need to sit around the table defining Business Glossary terms. So, the two or three IT employees have questions about what the word “invoice” means. Well, they can instant message or arrange a conversation with a manager or the person doubling as an account manager as to what that business term, among others, mean.  Second, the process of creating a Business Glossary can lead to quibbling about details on defining a term, taking away time and resources towards being productive in a business. Here are some alternatives to the Data Glossary.

• Start with a Data Dictionary: As Nicola Askham suggests in her article, use a Data Dictionary that has already been created and build the Business Glossary from there. In the process of building a Data Dictionary, stakeholders will be identified and business concepts will be hashed out as data elements are defined. Although, be aware that a Business Glossary, built using this approach, ties to a specific business context. As other business stakeholders identify different contexts and database systems the Business Glossary may need to be modified to cover these situations too. Remember a Business Glossary is driven by enterprise terminology not by specific terminologies.

• Reference a Business Glossary that has Already Been Created: Why reinvent the wheel? For example, say a business provides health insurance information to individuals or small employers. The U.S. Government has already created a glossary of typical health insurance terms. Want a report on expenditure per patient? Referring to this glossary, suggests differentiating between in-patient and out-patient care. Meet with stakeholders, IT engineers and choose a reliable Business Glossary, from a relatively unbiased source, that is available.

The Business Glossary – A Specific Study

In Data Dictionaries Demystified, Data Dictionaries provided a crucial tool to success of the Human Genome Project, as mentioned by Robert Robins . Towards that end, the National Cancer Institute (NCI) has made a Data Dictionary available through the Genetic Data Commons (GDC). The GDC makes this Data Dictionary available for cancer researchers to share data.  Researchers access the Data Dictionary through a Dictionary Viewer. Upon scanning the Data Dictionary Viewer, users can generate data files on “Masked Somatic Mutation” or “Exon Expression.” Unless the person reading the Dictionary Viewer understands how the business of genetics and its terminology works, this information can seem quite meaningless.

Upon consulting a Talking Glossary of Genetic Terms, as made available by the National Human Genome Research Institute, a user can make more sense of the data files generated from the Database System. The person can read about somatic cells and mutations in somatic cells or about “Exons” to get a better sense of what the data means in the GDC Data Dictionary.

A different user, new to genetics, who wishes to understand the genetics of Autism Spectrum Disorder may also use a Data Dictionary. The person could consult the NIMH Data Dictionary for Autistic Spectrum Disorder to find out what karyotype means in terms of autism genetic tests. A medical researcher could then look up karyotype in the Talking Glossary of Genetic Terms to get a better handle on karyotypes.

As the Talking Glossary of Genetic Terms demonstrates, understanding genetic terminology, central to its business, becomes essential in understanding the data elements in the Data Dictionary. The Business Glossary makes the technical terms described in a Data Dictionary more relevant to doing any job within that business.