Key organizational factors in data warehouse architecture selection

• Published in: Decision Support Systems Vol. 49; no. 2; pp. 200 - 212
• Main Authors: Ariyachandra, Thilini, Watson, Hugh
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 01-05-2010; Elsevier; Elsevier Sequoia S.A
• Subjects: Applied sciences; Archictecture selection; Architecture; Bus architecture; Computer science; control theory; systems; Computer systems and distributed systems. User interface; Data processing. List processing. Character string processing; Data warehouse architecture; Data warehouses; Data warehousing; Decision making; Decision support systems; Decision theory; Determinants; Enterprise data warehouse; Exact sciences and technology; Federated; Hub and spoke; Independent data marts; Information systems. Data bases; Logistics; Mathematical models; Memory organisation. Data processing; Regression; Regression analysis; Software; Studies; Bus architecture; Archictecture selection; Independent data marts; Data warehouse architecture; Data warehousing; Enterprise data warehouse; Federated; Hub and spoke; System architecture; Data analysis; Decision support system; Federated database; Modeling; Star network; Business process; Logistic regression; Binomial distribution; Field inquiry; Data warehouse; Firm
• ISSN: 0167-9236; 1873-5797
• DOI: 10.1016/j.dss.2010.02.006

Even though data warehousing has been in existence for over a decade, companies are still uncertain about a critical decision — which data warehouse architecture to implement? Based on the existing literature, theory, and interviews with experts, a research model was created that identifies the various contextual factors that affect the selection decision. The results from the field survey and multinomial logistic regression suggest that various combinations of organizational factors influence data warehouse architecture selection. The strategic view of the data warehouse prior to implementation emerged as a key determinant. The research suggests an overall model for predicting the data warehouse architecture selection decision.