A Bi-Directional Approach for Developing Data Warehouses in Public Sectors

Data warehouse is proclaimed as the latest decision support technology. As data warehouses require a significant amount of organizational resources to develop, more research have been devoted to identifying the critical success factors and the formulas for assured investment return from data warehouses. This study proposes a bi-directional development approach for data warehouses in public sectors. The primary rationale for the proposed approach is the fundamentally different organizational goals of public sector organizations from private sector organizations. Whereas the ultimate goal of private sector organizations is profit making, public sector organizations have a set of conflicting goals including different social and political objectives. The star schema as a dimensional data model for data warehouse is not totally suitable for data warehouses that demand the analyses of both quantitative and qualitative measures. Using the data warehouse in the College of Business Administration at the California State University, Sacramento as a case study, we illustrate how the QQ (Quantitative and Qualitative) data schema accommodates the need of capturing both quantitative and qualitative information. In addition, we show the bidirectional top-down/bottom-up initiative, the formal/informal information collection, and the enterprise data warehouse/subject data mart architecture for the data warehouse

Un enfoque gerencial de factores críticos para el éxito de los sistemas de información: Caso de estudio en PYMEs metalmecánicas venezolanas

Informes oficiales de países en desarrollo señalan, en general, significativas deficiencias en el tratamiento de la información en las pequeñas y medianas empresas (Pyme). Contar con sistemas de información automatizados (SI) es ineludible, pero es más importante que sean exitosos, para lo cual la satisfacción del usuario final es el factor clave que llevará a obtener los beneficios esperados. Los niveles gerenciales y los profesionales de informática deben estar familiarizados con los principales factores relacionados para asegurar su adecuado tratamiento. Este estudio evaluó la satisfacción del usuario final y varios factores críticos de éxito relacionados en una muestra de empresas industriales medianas (Pymi). Para ello, se utilizó uno de los modelos de éxito más reconocidos por la comunidad investigadora del área. Realizados los análisis cuantitativo/cualitativo y comparados los resultados se concluye que el principal factor relacionado con la satisfacción del usuario final es la calidad de la información, lo cual puede ser suficiente para considerar como exitoso un SI; con esto los demás factores quedan en segundo lugar. El beneficio práctico de esta investigación es reflexionar sobre estos factores, contribuir a reforzar la efectividad y calidad de los procesos de desarrollo o adquisición de un SI y reducir su índice de fracasos

Combining Website Search Engine Optimization with Advanced Web Log Analysis

This paper provides a clear guideline to the development of an online decision-making tool. The importance of ranking for an organizations virtual presence through search engines is also discussed. The system described illustrates the complexity of the competition between organizations to be highly ranked by leading search engines. The system not only reports the rankings of the owners but compares an organization with its competitors and enables it to decisively formulate an online development strategy in improving its ranking and therefore increasing its audience or critical mass. The system (Googalyser) utilizes Web logs and content analysis to provide decisive information to Web developers in order to improve the cases ranking through for example www.Google.com

An Exploratory Investigation of System Success Factors in Data Warehousing

Despite the increasing role of the data warehouse as a strategic information source for decision makers, academic research has been lacking, especially from an organizational perspective. An exploratory study was conducted to improve general understanding of data warehousing issues from the perspective of IS success. For this, the effect of variables pertaining to system quality, information quality, and service quality on user satisfaction for the data warehouse was studied. Additional characterization was made on data warehouse users, their organizational tasks, and data warehouse usage. Empirical data were gathered at a large enterprise from three different information sources: a survey, unstructured group interviews with end-users, and informal interviews with an IT manager who was in charge of the data warehouse. Data analysis showed that user satisfaction with the data warehouse was significantly affected by such system quality factors as data quality, data locatability, and system throughput. Interviews also supported the existence of system design and management issues that have to be addressed to optimize the utility of the data warehouse as an effective decision support environment. In the meantime, data analysis indicated that first-line (or lower) and middle managers were the main users of the system. Managers and knowledge workers were taking advantage of the system to perform complex tasks, to support decision making, and to seek information critical for enhanced productivity. The group interviews revealed additional benefits of the data warehouse and major roadblocks in its successful usage

Factors Influencing BI Data Collection Strategies: An Empirical Investigation

The purpose of this dissertation is to examine the external factors that influence an organizations' business intelligence (BI) data collection strategy when mediated by BI attributes. In this dissertation, data warehousing strategies are used as the basis on which to frame the exploration of BI data collection strategies. The attributes include BI insightfulness, BI consistency, and the organizational transformation attribute of BI. The research population consisted of IT professionals and top level managers involved in developing and managing BI. Data was collected from a range of industries and organizations within the United States. An online survey was used to collect the data to empirically test the proposed relationships. Data was analyzed using partial least square path modeling (PLS). The results of this study suggest that there exists a positive relationship between institutional isomorphism and BI consistency. The results also indicate that there exists a positive relationship between BI consistency and BI comprehensive data collection strategy, and the organizational transformation attribute of BI and BI comprehensive data collection strategy. These findings provide a theoretical lens to better understand the motivators and the success factors related to collecting the huge amounts of data required for BI. This study also provides managers with a mental model on which to base decisions about the data required to accomplish their goals for BI

Approaches to selecting information systems projects under uncertainty

The rapid advance in information and communication technologies has effectively facilitated the development and implementation of information systems (IS) projects in modern organizations for reorganizing their business processes and streamlining the provision of their products and services in today's dynamic environment. Such a development brings organizations with numerous benefits including increased automation of business processes, improved customer service, and timely provision of effective decision support. As a result, evaluating and selecting the most appropriate IS project for development and implementation from a pool of available IS projects becomes a critical decision to make in modern organizations. Evaluating and selecting appropriate IS projects for development in an organization, however, is complex and challenging. The complexity of the evaluation and selection process is due to the multi-dimensional nature of the decision making process, the conflicting nature of the multiple selection criteria, and the presence of subjectiveness and imprecision of the human decision making process. The challenging of the evaluation and selection comes from the need for making transparent and balanced decisions based on a comprehensive evaluation of all available IS projects in a timely manner. Much research has been done on the development of various approaches for evaluating and selecting IS projects, and numerous applications of those approaches for addressing real world IS project evaluation and selection problems have been reported in the literature. In general, existing approaches can be classified into (a) cost-benefit analysis based approaches, (b) utility based approaches, and (c) optimization oriented approaches. These approaches, however, are not totally satisfactory due to various shortcomings including (a) the inability to tackle the subjectiveness and imprecision of the selection process, (b) the failure to adequately handle the multi-dimensional nature of the problem, and (c) cognitively very demanding on the decision maker. To address these issues above, this research has developed three novel approaches for effectively solving the IS project evaluation and selection problem under uncertainty in an organization. The first approach is developed for helping the decision maker better model the subjectiveness and imprecision inherent in the decision-making process with the use of linguistic variables approximated by fuzzy numbers. The second approach is designed to reduce the cognitive demanding on the decision maker in the IS project evaluation and selection process with the introduction of fuzzy pairwise comparison. The third approach is formulated with respect to the use of intelligent decision support systems for facilitating the use of specific multi-criteria analysis approaches in relation to individual IS project evaluation and selection situations. The developed approaches have been applied for solving three IS project evaluation and selection problems in the real world settings. The results show that the three developed ap proaches are of practical significance for effectively and efficiently solving the IS project evaluation and selection problem due to (a) the simplicity and comprehensibility of the underlying concept, (b) the adequate handling of inherent uncertainty and imprecision, and (c) the ability to help the decision maker better understand the IS project selection problem and the implications of their decision behaviours