DATA WAREHOUSING

Data Warehousing & Its Effects On Decision-Making Processes In Sporting Industries

Data Warehousing & Its Effects On Decision-Making Processes In Sporting Industries

Introduction

Sporting Industry establishes a decision warehousing based decision support system infrastructure to support individual decision-making. While the effectiveness of this type of infrastructure has been discussed from conceptual and technical perspectives, less focus has been applied to how a decision warehousing based decision support system infrastructure and its three components actually facilitate decision-making. The current literature describes how each component can support decision-making but does not document the support being provided in real decision warehousing based - decision support system. The following research question focuses on how decision-making is supported by the decision warehousing based decision support system infrastructure components.

The decision support systemdecision performance model was developed and validated in a controlled, experimental setting. Because the model has not been operational in an applied setting, the dimensions for each construct have not been identified. For example, in the experiments, the capabilities and task constructs were held constant or controlled, and individual dimensions for these constructs were not developed (Gorla, 2003). The following research question addresses the external validity of this model and represents an initial step towards operationally the model in a decision warehousing based decision support system environment

Characteristics of decision warehousing based decision support system Decision Environments decision warehousing based decision support system applications represent a complex, heterogeneous decision-making environment and possess unique characteristics. During our review of the literature, three characteristics emerged that are specific to the decision warehousing based decision support system environment as compared to a traditional decision support system environment. First, the heterogeneity of the data sources that populate a data warehouse has prompted the need to correctly interpret these data, particularly at the analytical user level (Ballou & Tayi, 1999). The primary means for accomplishing this goal are through the use of metadata, which is descriptive data about the data available in an information system. Practitioners and researchers continually stress the importance of metadata in a data warehousing environment, and have observed that without it, users will avoid using the data warehouse or will use it inefficiently. Second, as data are pushed out to end user decision-makers, these end users require more explanations of the data.

The general goal of this project, to investigate how decision warehousing based decision support system provide decision support to individual decision makers, requires a unit of analysis at the individual decision-maker level. Individual decisionmakers using a live decision warehousing based decision support system were thus the subjects of our analysis (Sen & Sinha, 2005). A multiple case study design was used to improve reliability given the numerous external, uncontrolled conditions that could influence each individual's decision-making behavior. The study was replicated eight times, as four users of the enabling technologies component (analysts) and four users of the applications solution component (end-users) served as a case study subjects (Naughton-Travers, 1998). Care was taken to include both experienced and inexperienced decision-makers in our case study as experience has been shown to ...