Data Model Performance in Data Warehousing

2nd International Conference on Innovation in Engineering and Vocational Education

工业技术;教育

Rorimpandey, G.C.^1 ; Sangkop, F.I.^1 ; Rantung, V.P.^1 ; Zwart, J.P.^2 ; Liando, O.E.S.^1 ; Mewengkang, A.^1

Department of Informatics, Universitas Negeri Manado, Jl. Kampus FT, Unima Tondano, North Sulawesi

95618, Indonesia^1

HAN University of Applied Scieces, Ruitenberglaan 31, CC Arnhem

6826, Netherlands^2

关键词: Analysis of data;    Data collection;    Descriptive analysis;    Interpretation of data;    Model performance;    research methods;    Statistic analysis;    Statistical differences;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/306/1/012044/pdf
DOI  :  10.1088/1757-899X/306/1/012044

来源: IOP

【 摘 要 】

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.