2026-09-20T03:44:41Zhttps://dspace.mit.edu/server/oai/request

oai:dspace.mit.edu:1721.1/1452442025-10-30T17:51:25Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023

Patrick Hale. Soni, Rupreet Singh. Massachusetts Institute of Technology. Engineering Systems Division. System Design and Management Program. Massachusetts Institute of Technology. Engineering Systems Division System Design and Management Program. 2022-08-31T16:29:47Z 2022-08-31T16:29:47Z 2013 2013 https://hdl.handle.net/1721.1/145244 1342111189 Thesis: S.M. in Engineering and Management, Massachusetts Institute of Technology, Engineering Systems Division, System Design and Management Program, 2013 Cataloged from PDF version of thesis. Includes bibliographical references (pages 61-64). These days mostly all data generated is stored as digital data. Whatever action happens in the world, the outcome tends to be a digital data. From social networking sites to customer management applications and to further different business segments and operational streams of the organizations, everything formulates to be a digital data. For organizations, data is generated from different business sectors and varied operational segments. The question that is prevalent and is hard to answer is how do organizations take best holistic decisions on data sets coming from varied applications and source systems. To take effective decisions, organizations need to collate the data coming from different source systems and create a unified master data. Decisions taken on such master records are more meaningful and impactful. Master Data Management is a technology that helps organizations to collate varied data sets originating from different source systems and create a unified master data set. This master data set can be further used by the organizations for effective analytics, operational benefits, streamlined reporting and even for adhering to regulatory requirements. Organizations can collate several different types of data entities and hence Master Data Management can be applied on different domains such as customers, suppliers, products and vendors. It depends on an organizational requirement for which domain data sets need to be collated and mastered. Thesis is divided into 3 segments. First segment describes the Master Data Management technology and gives an overview of the architecture and snapshot of industry adoption of the technology. Second chapter describes the motivational factors for organizations to use Master Data Management. Last and third chapter describes a strategic framework to implement Master Data Management in an organization. Finally I have drawn few conclusions out of my thesis, which help to understand the thesis appropriately. by Rupreet Singh Soni. S.M. in Engineering and Management S.M. in Engineering and Management Massachusetts Institute of Technology, Engineering Systems Division, System Design and Management Program 64 pages eng Massachusetts Institute of Technology MIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided. http://dspace.mit.edu/handle/1721.1/7582 Engineering Systems Division. System Design and Management Program. Role of master data management in large organizations Thesis application/pdf 2022-08-31T16:29:47Z Publication Master Sloan unknown unknown <Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="cc8440ed-6424-479e-a7e9-b7cd9293c181"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Language>eng</Language> <Title>Role of master data management in large organizations</Title> <PublishedIn> <Publication> </Publication> </PublishedIn> <PublicationDate>2013</PublicationDate> <Authors> <Author> <DisplayName>Soni, Rupreet Singh.</DisplayName> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>Massachusetts Institute of Technology</DisplayName> <OrgUnit /> </Publisher> </Publishers> <License>http://dspace.mit.edu/handle/1721.1/7582</License> <Keyword>Engineering Systems Division.</Keyword> <Keyword>System Design and Management Program.</Keyword> <Abstract>These days mostly all data generated is stored as digital data. Whatever action happens in the world, the outcome tends to be a digital data. From social networking sites to customer management applications and to further different business segments and operational streams of the organizations, everything formulates to be a digital data. For organizations, data is generated from different business sectors and varied operational segments. The question that is prevalent and is hard to answer is how do organizations take best holistic decisions on data sets coming from varied applications and source systems. To take effective decisions, organizations need to collate the data coming from different source systems and create a unified master data. Decisions taken on such master records are more meaningful and impactful. Master Data Management is a technology that helps organizations to collate varied data sets originating from different source systems and create a unified master data set. This master data set can be further used by the organizations for effective analytics, operational benefits, streamlined reporting and even for adhering to regulatory requirements.</Abstract> <Abstract>Organizations can collate several different types of data entities and hence Master Data Management can be applied on different domains such as customers, suppliers, products and vendors. It depends on an organizational requirement for which domain data sets need to be collated and mastered. Thesis is divided into 3 segments. First segment describes the Master Data Management technology and gives an overview of the architecture and snapshot of industry adoption of the technology. Second chapter describes the motivational factors for organizations to use Master Data Management. Last and third chapter describes a strategic framework to implement Master Data Management in an organization. Finally I have drawn few conclusions out of my thesis, which help to understand the thesis appropriately.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication>