A business glossary done right can be a directory of the importance of data to the business, with specialized definitions and relationships. It can democratize the understanding of specific data, terms and processes in the enterprise. It’s obvious why this is useful, but most implementations of business glossary leave value on the table and fail to enable data users.
What makes a Valuable Business Glossary?
Defined Business Terms: Business glossaries must contain a list of all business terms and their associated definitions. This must account for terms which mean different things to different areas of the business to eliminate ambiguity.
Contextualization: A valuable business glossary must place each term in both its data and business context. It must be easy for a user to view where the term fits into the data system and process landscape of the enterprise to properly understand its importance to the business.
Advanced Search: Without advanced search, it’s almost futile to implement a business glossary. Enterprises have thousands of terms, often similar or duplicate to one another, that must be mapped and accessible. Search that can be augmented with intelligent filters drawn from metadata is a must.
Data Protection: Data governance policies must be associated to terms within the business glossary, and visible within the broader contextualization. This ensures that different classifications of sensitive data can be made, and protection processes are always visible and followed.
What are the Advantages?
Business glossaries allow organizations to define business terms and create a shared business language across its different departments. The term ‘customer’ is the perfect example. It could mean an individual who buys a product, or another business that is paying for a service. Different areas in the LOB would view customers in different ways. Business glossaries ensure there is no miscommunication between departments by putting clear definitions that are applicable throughout the whole organization. An example of a definition would be that a ‘customer’ is an individual who purchases, or has the potential to purchase, goods or services from a ‘retailer’. This would clarify that the business term ‘customer’ is someone who buys from the retailer, as opposed to a retailer buying from a supplier and any other meaning the term ‘customer’ may have. The term ‘retailer’ would also be defined in the business glossary for absolute clarity.
Data citizens are able to make more informed decisions by using business glossaries. This is done by contextualising important information other than business terms such as key performance indicators (KPIs), objectives and key results (OKR) or any other data assets applicable. Ownership of content or accountability can be established through the business glossary if it is suitable to the business. Data owners can imbue certain terms and the information attributed to them with legitimacy by verifying or signing off on them. Drawing back to the ‘customer’ example, this term can be contextualised with reference data explaining what demographics the business’ customers are in (age, race, country) and the data owner who sourced the data.
Businesses can ensure they remain compliant with regulatory requirements through implementing their terms with data governance policies and classifications. Again returning to the term ‘customer’ as an example, sensitive information regarding customers would necessitate policies and a level of classification to access it. Business glossaries can be set up so that information such as a customer’s address, billing history or payment information can be accessed by data citizens who need it for their work and have the proper training to be trusted with such information.
Ultimately, the business glossary improves an organization’s efficiency. By creating a shared business language, collaboration across departments within a business becomes harmonious. Employees are enabled to perform their work functions without the need to locate the information they need as it is readily available with a search.
Getting Maximum Value from your Business Glossary
Business glossaries have traditionally been built and maintained manually. Defining each term requires a lengthy process which can be simplified into identifying data owners, gathering intelligence related to the term, preparing a draft definition, consulting experts and then seeking approval from the data owner. This process can be significantly minimized through leveraging machine learning to render these steps much easier or completely automated. To ensure that a business glossary is constructed with the qualities of a good business glossary mentioned above, integrating enterprise level metadata management that offers powerful automation and best-in-class features, like the Alex Platform, is imperative.
An intelligent business glossary that utilises AI ensures that it will be accurate. Any existing business glossary can be seamlessly transitioned into one that can contend with today’s Big Data. With the world’s largest number of native connectors at Alex’s disposal, metadata throughout an organization can be automatically harvested, defined and classified. In order to fully draw out benefits from a business glossary, it should be used in conjunction with other tools to establish a concrete metadata management framework. Alex is designed so its features function together to synergistically bolster each other.
A business glossary that has been integrated with Alex is granted the assurance of sophisticated Data Securitythat constantly protects its data from mishandling inside an organization and the malicious forces outside. It links business terms within the glossary to data assets that are stored in the Augmented Data Catalogso they can be accessed easily. Additionally, Alex’s Data Lineageprovides automated mapping of data flows, providing insights to information in the business glossary that is easily digestible. To learn more about how to get value out of your business glossary please request a demo below.