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Abstract
The IT implementation literature suggests that various implementation factors play critical roles in the success of an information system; however, there is little empirical research about the implementation of data warehousing projects. Data warehousing has unique characteristics that may impact the importance of factors that apply to it. In this study, a cross-sectional survey investigated a model of data warehousing success. Data warehousing managers and data suppliers from 111 organizations completed paired mail questionnaires on implementation factors and the success of the warehouse. The results from a Partial Least
Squares analysis of the data identified significant relationships between the system quality and data quality factors and perceived net benefits. It was found that management support and resources help to address organizational issues that arise during warehouse implementations; resources, user participation, and highly-skilled project team members increase the likelihood that warehousing projects will finish on-time, on-budget, with the right functionality; and diverse, unstandardized source systems and poor development technology will increase the technical issues that project teams must overcome. The implementation's success with organizational and project issues, in turn, influence the system quality of the data warehouse; however, data quality is best explained by factors not included in the research model.
Keywords: Data warehousing, success, IS implementation, Partial Least Squares
ISRL Categories: HA03, FD, A10610, EL03
Introduction
During the mid- to late 1990s, data warehousing became one of the most important developments in the information systems field. It is estimated that 95% of the Fortune 1000 companies either have a data warehouse in place or are planning to develop one (META Group 1996). The Palo Alto Management Group predicts that the data warehousing market will grow to a $113.5 billion market in 2002, including the sales of systems, software, services, and in-house expenditures (Eckerson 1998). This is not surprising considering that for the past few years, surveys of ClOs have found data warehousing, Year 2000, and electronic commerce to be at the top of their strategic initiatives (Eckerson 1999).
A data warehouse (or smaller-scale data mart) is a specially prepared repository of data created to support decision making. Data are extracted from source systems, clean ed/scrubbed, transformed, and placed in data stores (Gray and Watson 1998). A data warehouse has data suppliers...