DATA WAREHOUSE AND BUSINESS INTELLIGENCE STRATEGIES AND TRENDS

In recent decades following the evolution of information technology, decision support systems have played an important role by presenting the necessary information resulted from the operational systems processes. By continuing improvement of the methods as well as the contribution of technological advance the applicability of decision support systems is now generalized and has reached the status of complex systems of business intelligence. Business Intelligence is about creating intelligence about a business based on a cyclic flow which consists of capturing, analyzing, planning and implementation resulting in streamlining the organization.Decisions, DSS, Data Driven, Business Intelligence, Data Warehouse

Addressing business agility challenges with enterprise systems

It is clear that systems agility (i.e., having a responsive IT infrastructure that can be changed quickly to meet changing business needs) has become a critical component of organizational agility. However, skeptics continue to suggest that, despite the benefits enterprise system packages provide, they are constraining choices for firms faced with agility challenges. The reason for this skepticism is that the tight integration between different parts of the business that enables many enterprise systems\u27 benefits also increases the systems\u27 complexity, and this increased complexity, say the skeptics, increases the difficulty of changing systems when business needs change. These persistent concerns motivated us to conduct a series of interviews with business and IT managers in 15 firms to identify how they addressed, in total, 57 different business agility challenges. Our analysis suggests that when the challenges involved an enterprise system, firms were able to address a high percentage of their challenges with four options that avoid the difficulties associated with changing the complex core system: capabilities already built-in to the package but not previously used, leveraging globally consistent integrated data already available, using add-on systems available on the market that easily interfaced with the existing enterprise system, and vendor provided patches that automatically updated the code. These findings have important implications for organizations with and without enterprise system architectures

Building a Data Warehouse step by step

Data warehouses have been developed to answer the increasing demands of quality information required by the top managers and economic analysts of organizations. Their importance in now a day business area is unanimous recognized, being the foundation for developing business intelligence systems. Data warehouses offer support for decision-making process, allowing complex analyses which cannot be properly achieved from operational systems. This paper presents the ways in which a data warehouse may be developed and the stages of building it.data warehouse, data mart, data integration, database management system, OLAP, data mining

High Performance HR Practices And Customer Satisfaction: Employee Process Mechanisms

This research examined organizational commitment and customer focus as mediators between HR practices and customer satisfaction of seventy-one work units from twenty-five business units from a single firm in the food service industry. Customer satisfaction was assessed by ratings from multiple customers eighteen months after HR practices and process mechanisms were assessed from unique groups of employee respondents. Results suggest that employee commitment and customer focus partially mediate the relationship between HR practices and customer satisfaction

Implementation System of Business Intelligence System In The Company

This study aims to determine the stages that must be implemented in building a Business Intelligence System structured and appropriate in building Business Intelligence Systems in an organization, and understand the important aspects that must be considered for investment development Business Intelligence System is increasing. Business must be based on the conditions and needs of the organization in achieving the desired goals. If these conditions occur, then the decision-making process will be better and more accurate. The purpose of this study is to determine the important aspects that must be understood and prepared in using the Business Intelligence System in an organization. The method used is the explanation as well as the research library of several books, articles and other literature

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

BCAS: A Web-enabled and GIS-based Decision Support System for the Diagnosis and Treatment of Breast Cancer

For decades, geographical variations in cancer rates have been observed but the precise determinants of such geographic differences in breast cancer development are unclear. Various statistical models have been proposed. Applications of these models, however, require that the data be assembled from a variety of sources, converted into the statistical models’ parameters and delivered effectively to researchers and policy makers. A web-enabled and GIS-based system can be developed to provide the needed functionality. This article overviews the conceptual web-enabled and GIS-based system (BCAS), illustrates the system’s use in diagnosing and treating breast cancer and examines the potential benefits and implications for breast cancer research and practice

Correlating Architecture Maturity and Enterprise Systems Usage Maturity to Improve Business/IT Alignment

This paper compares concepts of maturity models in the areas of Enterprise Architecture and Enterprise Systems Usage. We investigate whether these concepts correlate, overlap and explain each other. The two maturity models are applied in a case study. We conclude that although it is possible to fully relate constructs from both kinds of models, having a mature architecture function in a company does not imply a high Enterprise Systems Usage maturity

Business intelligence in the electrical power industry

Nowadays, the electrical power industry has gained tremendous interest from both entrepreneurs and researchers due to its essential roles in everyday life. However, the current sources for generating electricity are astonishing decreasing, which leads to more challenges for the power industry. Based on the viewpoint of sustainable development, the solution should maintain three layers of economically, ecologically, and society; simultaneously, support business decision-making, increases organizational productivity and operational energy efficiency. In the smart and innovative technology context, business intelligence solution is considered as a potential option in the data-rich environment, which is still witnessed disjointed theoretical progress. Therefore, this study aimed to conduct a systematic literature review and build a body of knowledge related to business intelligence in the electrical power sector. The author also built an integrative framework displaying linkages between antecedents and outcomes of business intelligence in the electrical power industry. Finally, the paper depicted the underexplored areas of the literature and shed light on the research objectives in terms of theoretical and practical implications