Overview of glossary models

A glossary model is a model that describes the names and abbreviations that an organization allows for data objects. A glossary model also defines prime words (such as Employee or Company), class words (such as Name or Employee ID), and modifiers (such as First or Annual).

Sometimes, when working with various people on the same project, data object naming varies. Where one data architect might refer to sales entities as SALES_x, another data modeler might prefer SLS_x. Over time, the system becomes difficult to understand, and the inconsistency can spread across systems, causing confusion, longer application development times, or even the inability to make the connection between two fields that mean the same thing in two different systems.

To avoid this problem, you should develop a set of naming standards early in the data design process. Naming standards help you and other people in your organization look at your data in a consistent manner, so that you all get the same meaning. With the workbench, you can create a set of rules that all data modelers should follow, and the workbench can automatically create names of some of the data objects (such as relationships) for you.

A glossary model is a model that describes the names and abbreviations that an organization allows for data objects. Data object naming standards promote a common understanding of data, since you use the same name conventions across the entire organization. You can use glossary models to enable sharing of data across organizational boundaries and reduce data redundancy through the consolidation of synonymous and overlapping data elements.

When you name a data object, you need to take into account two items: semantic rules and format. Semantically, glossary model objects include prime words, class words, and modifiers:
Names
Names are what you use to describe abbreviations, prime words, class words, and modifiers. You can use common language, such as Account Name or Employee ID Number to describe these types of data.
Abbreviations
Abbreviations are the standard abbreviations that you want to use for data objects in the model. For example, your organization wants to use the EMPLOYEE abbreviation and the EMP alternate abbreviation to specify data objects that model employee-related information.
Prime words
Prime words are words that represent the business concept about which data is being collected. Prime words are nouns that describe the subject area of the data. For example, the LOAN prime word specifies that all data objects that use this prime word are related to the loan.
Class words
Class words are words that identify a distinct category or classification of data. For example: RATE, NAME
Modifiers
Modifiers are words that further qualify or distinguishes the prime and class words. It helps make the object name clear and unique, and it can help restrict the meaning of the class and prime words. For example: NEXT, FIRST

You can use a glossary model in the following ways:

In addition to glossary model entries, data object naming standards are specified on the Data > Naming Standards Preferences page. These preferences are also used during data model analysis.

Using the workbench, you can:

Glossary models are stored in data design projects. You can share one glossary model among multiple data design projects. A glossary model file has the extension *.ndm.


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