Master Data Management (MDM) programs offer many benefits to enterprises. Primary among them is greater control over reference data and the capability to manage the relations between data entities. However, to translate the benefits from MDM programs into effective business knowledge, there should be an understanding and agreement on the terminologies used inside an enterprise. Enterprises can achieve both by leveraging taxonomies.
Taxonomy helps an enterprise overcome the twin challenges inherent in MDM architecture—ambiguity and inconsistency. It eliminates ambiguity by offering a hierarchy and mechanisms for understanding the context and making meanings precise. Therefore, even if a term has many meanings, a taxonomy enables employees along the length and breadth of an enterprise to understand what is being addressed.
The challenge regarding inconsistency arises from the fact that it is difficult to get employees to agree on what term to employ. A way for overcoming this inconsistent use of terms is by using a thesaurus to map terms together. Another way is deploying taxonomies, which are technically a part of a thesaurus, to represent related concepts, which can be subsequently used to connect processes, business logic, or dynamic/related content to support specific tasks.
Furthermore, enterprises are exploring methods to broaden the scope of the use cases and make greater use of analytics by assimilating data from multiple domains. Consequently, taxonomies become more of a necessity for enterprises for maximizing the benefits accruing from deploying MDM programs. For instance, to conduct analytics across domains and develop effective governance programs, enterprises need to set up consistent taxonomies and standard metadata, especially for critical data. The data models also need to reflect a consistent taxonomy. Further, through an ontology, the relationships between the various taxonomies can be captured and documented. To sum up, taxonomies help an enterprise to maximize the benefits of MDM programs.
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