Please use this identifier to cite or link to this item: http://localhost:8080/xmlui/handle/123456789/35
Title: Data Model Performance in Data Warehousing
Authors: Rorimpandey, Gladly Caren
Sangkop, Ferdinan Ivan
Rantung, Vivi Peggie
Zwart, J P
Liando, Olivia Eunike Selvie
Mewengkang, Alfrina
Issue Date: 22-Feb-2018
Publisher: IOP Publishing Ltd
Citation: G C Rorimpandey et al 2018 IOP Conf. Ser.: Mater. Sci. Eng. 306 012044
Series/Report no.: IOP Conf. Series: Materials Science and Engineering;306
Abstract: Data Warehouses have increasingly become important in organizations that have large amount of data. It is not a product but a part of a solution for the decision support system in those organizations. Data model is the starting point for designing and developing of data warehouses architectures. Thus, the data model needs stable interfaces and consistent for a longer period of time. The aim of this research is to know which data model in data warehousing has the best performance. The research method is descriptive analysis, which has 3 main tasks, such as data collection and organization, analysis of data and interpretation of data. The result of this research is discussed in a statistic analysis method, represents that there is no statistical difference among data models used in data warehousing. The organization can utilize four data model proposed when designing and developing data warehouse.
URI: http://localhost:8080/xmlui/handle/123456789/35
Appears in Collections:Lecturer Scientific Papers

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