Architectural Evaluation of Master Data Management (MDM): Literature Review
Abstract: Architectural evaluation of MDM data models are influenced by technical assessment, business requirements, and designers’ preferences. Therefore, selecting the right model for an organization requires quantitative method with qualitative embedded design study. Greene  states that three purposes of quantitative study with embedded qualitative design include 1) triangulation, to guarantee or attain validation of data, or convergent validation; 2) complimentarily, to elucidate, clarify, or otherwise more fully detailed the results of analyses; and 3) development, to lead the use of additional sampling data gathering, and analysis procedures (p. 259). The existing literature demonstrates the need for both qualitative and quantitative design analysis to describe the relationship between MDM architectural models’ alternatives (federated and centralized).
Current literature studies do not dispute the importance of MDM models and their relationships to the single view of organization’s master data. The IT community unanimously supports the notation of “single view of organization’s master data.” According to Rosenberg , master data forms the basis for the business process; Loshin claims that the main goal of designing any MDM is to ensure that the system is business driven. Loshin  considers the implementation MDM a failure if it fails to address the business needs (p. 54). This paper documents the importance of literature study to support the need for qualitative and quantitative analysis.
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