An Open Source Based Data Warehouse Architecture to Support Decision Making in the Tourism Sector

In this paper an alternative Tourism oriented Data Warehousing architecture is proposed which makes use of the most recent free and open source technologies like Java, Postgresql and XML. Such architecture's aim will be to support the decision making process and giving an integrated view of the whole Tourism reality in an established context (local, regional, national, etc.) without requesting big investments for getting the necessary software.Tourism, Data warehousing architecture

On the impact of Knowledge Discovery and Data Mining

Knowledge Discovery and Data Mining are powerful automated data analysis tools and they are predicted to become the most frequently used analytical tools in the near future. The rapid dissemination of these technologies calls for an urgent examination of their social impact. This paper identifies social issues arising from Knowledge Discovery (KD) and Data Mining (DM). An overview of these technologies is presented, followed by a detailed discussion of each issue. The paper's intention is to primarily illustrate the cultural context of each issue and, secondly, to describe the impact of KD and DM in each case. Existing solutions specific to each issue are identified and examined for feasibility and effectiveness, and a solution that provides a suitably contextually sensitive means for gathering and analysing sensitive data is proposed and briefly outlined. The paper concludes with a discussion of topics for further consideration

The local economic development processes in low-income countries: the case of the metropolis of Chegutu in Zimbabwe

Local authorities are widely regarded as catalysts accelerating localised processes of economic development in industrialised countries but in low-income countries they are perceived as dysfunctional, inefficient and ineffective in meeting and addressing societal demands. This abstract view is however, not grounded in empirical research. As such, utilising the case of the metropolis of Chegutu a survey was designed to empirically explicate the economic processes militating its economic development. The findings are useful to policy-makers, local government authorities and management scholars. The study's unique contribution lies in its examination of the processes of local economic development in a low-income country

Big Data, Bigger Dilemmas: A Critical Review

The recent interest in Big Data has generated a broad range of new academic, corporate, and policy practices along with an evolving debate among its proponents, detractors, and skeptics. While the practices draw on a common set of tools, techniques, and technologies, most contributions to the debate come either from a particular disciplinary perspective or with a focus on a domain-specific issue. A close examination of these contributions reveals a set of common problematics that arise in various guises and in different places. It also demonstrates the need for a critical synthesis of the conceptual and practical dilemmas surrounding Big Data. The purpose of this article is to provide such a synthesis by drawing on relevant writings in the sciences, humanities, policy, and trade literature. In bringing these diverse literatures together, we aim to shed light on the common underlying issues that concern and affect all of these areas. By contextualizing the phenomenon of Big Data within larger socioeconomic developments, we also seek to provide a broader understanding of its drivers, barriers, and challenges. This approach allows us to identify attributes of Big Data that require more attention—autonomy, opacity, generativity, disparity, and futurity—leading to questions and ideas for moving beyond dilemmas

Where are we headed in business analytics? A framework based on a paradigmatic analysis of the history of analytics

The explosion of interest in business analytics (BA) comes with multiple problems. With as many as eleven distinct disciplines teaching analytics, it is not clear which areas of study constitute the BA field. If the information systems (IS) field is to exert a significant influence in analytics, what the IS researcher and practitioner need to focus on has to be made clear. Using a paradigmatic historiographical analysis of the field of analytics this study provides evidence for the bifurcation of analytics into data science and BA as founding disciplines of computer science, mathematics and statistics, machine learning and IS contribute to the analytics movement. The results from this analysis also identify a set of conceptual foundations for BA that takes advantage of both the intellectual strengths of the IS field without sacrificing the necessary depth of data science

MSIS 2006: Model Curriculum and Guidelines for Graduate Degree Programs in Information Systems

This article presents the MSIS 2006 Model Curriculum and Guidelines for Graduate Degree Programs in Information Systems. As with MSIS 2000 and its predecessors, the objective is to create a model for schools designing or revising an MS curriculum in Information Systems. The curriculum was designed by a joint committee of the Association for Information Systems and the Association for Computing Machinery. MSIS2006 is a major update of MSIS 2000. Features include increasing the number of required courses from 10 to 12 while revising prerequisites, introducing new courses and revising existing courses to modernize the curriculum, and alternatives for phased upgrading from MSIS2000 to MSIS 2006. As with the previous curriculum, it is the product of detailed consultation with the IS community. The curriculum received the endorsement of 8 major IS professional groups

Unveiling the Potential of Big Data Analytics for Transforming Higher Education in Bangladesh; Needs, Prospects, and Challenges

Big Data Analytics has gained tremendous momentum in many sectors worldwide. Big Data has substantial influence in the field of Learning Analytics that may allow academic institutions to better understand the learners needs and proactively address them. Hence, it is essential to understand Big Data and its application. With the capability of Big Data to find a broad understanding of the scientific decision making process, Big Data Analytics (BDA) can be a piece of the answer to accomplishing Bangladesh Higher Education (BHE) objectives. This paper reviews the capacity of BDA, considers possible applications in BHE, gives an insight into how to improve the quality of education or uncover additional values from the data generated by educational institutions, and lastly, identifies needs and difficulties, opportunities, and some frameworks to probable implications about the BDA in BHE sector. Keywords; Big Data Analytics, Learning Analytics, Quality of Education, Challenges, Higher Education, Banglades

Retail Inventory Control Strategies

Despite using computerized merchandise control systems in retail, the rate of stockouts has remained stagnant. The inability to satisfy customer needs has caused a loss of 4% in potential revenue and resulted in dissatisfied customers. The purpose of this qualitative multiple case study was to explore cost-effective inventory control strategies used by discount retail managers. The conceptual framework that grounded the study was chaos theory, which helped identify why some business leaders rely on forecasting techniques or other cost-effective strategies as an attempt to prevent stockouts. The target population was comprised of discount retail managers located throughout northeast Jacksonville, Florida. Purposeful sampling led to selecting 6 retail managers who successfully demonstrated cost-effective inventory control strategies for mitigating stockouts. Data were collected through face-to-face semistructured interviews, company websites, and company documents. Analysis included using nodes to identify similar words and axial-coding to categorize the nodes into themes. Transcript evaluation, member checking, and methodological triangulation strengthened the credibility of the findings. Five themes emerged: (a) internal stockout reduction strategies, (b) external stockout reduction strategies, (c) replenishment system strategies, (d) inventory optimization strategies, and (e) best practices for inventory control. This study may contribute to positive social change by improving inventory management, which may reduce demand fluctuations in the supply chain and reduce logistics costs in the transportation of freight thereby leading to improved customer satisfaction