An enterprise master data model based on the data taxonomy based on their origin

Mi Young Choi, Chang Joo Moon, Ki Seok Park, Doo Kwon Baik

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Master data provides business consistency and data integrity to different data systems when multiple IT systems across an organization (or beyond) identify the same entity differently. Master data can support transactional processes and operations. In addition, analytics/reporting are another area greatly dependent on an organization's master data. Therefore, master data represents core information, and organizations should consider it to be an important asset. Building a structure of each master data and representing an integrated data model are the main tasks of master data management. However, most research thus far has concentrated on data flow and data standards for building the physical environment of a centrally controlled master data management system. Only partial logical models with specific entities have been suggested, even for a master data model. This paper suggests an enterprise master data model (EMDM) which defines all of the master data composition elements, the hierarchical structure in each master data element, and the relationship between master data elements across the organization. The origin data taxonomy methodology was adopted to represent the master data elements and hierarchical structure. A case study demonstrates the proposed enterprise master data model (EMDM) applied to an insurance business.

Original languageEnglish
Title of host publicationInternational Conference on Enterprise Information Systems and Web Technologies 2010, EISWT 2010
Pages34-41
Number of pages8
Publication statusPublished - 2010
Event2010 International Conference on Enterprise Information Systems and Web Technologies, EISWT 2010 - Orlando, FL, United States
Duration: 2010 Jul 122010 Jul 14

Publication series

NameInternational Conference on Enterprise Information Systems and Web Technologies 2010, EISWT 2010

Other

Other2010 International Conference on Enterprise Information Systems and Web Technologies, EISWT 2010
CountryUnited States
CityOrlando, FL
Period10/7/1210/7/14

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems

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  • Cite this

    Choi, M. Y., Moon, C. J., Park, K. S., & Baik, D. K. (2010). An enterprise master data model based on the data taxonomy based on their origin. In International Conference on Enterprise Information Systems and Web Technologies 2010, EISWT 2010 (pp. 34-41). (International Conference on Enterprise Information Systems and Web Technologies 2010, EISWT 2010).