Data Governance Of Master Data Management

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Data Governance in Master Data Management
Introduction
Organizations are required to adapt to their business models. Global presence requires a harmonized business process across different continents where the customers ask for individualized products, and service offerings must be industrialized. All these factors affect the business process architecture and the IT strategy of the organizations. Data of high quality are a prerequisite for fulfilling continuously changing business needs and achieving enterprise agility objectives. Surveys on data warehousing failures reveal that organizational rather than technical issues are more critical to their success. The organizational issues that must be addressed such as maintaining sponsorship, managing expectation and compliance, defining accountabilities, avoiding scope creep and handling political issues push Data Quality Management into an area of conflict between business and IT [1, 3]. Governance is a formal process of assigning roles and responsibilities that are commensurate with the levels of authority and accountability in the organization [5].
Master Data Management is a workflow-driven process in which business units and IT collaborate to harmonize, cleanse, publish and protect common information assets that must be shared across the enterprise. MDM ensures the consistency, accuracy, stewardship and accountability for the core information of the enterprise [7]. Master data governance necessitates the definition of
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