Big Data analysis is the process that can help organizations to make better business decisions. Organizations use data warehouses and business intelligence systems, i.e. enterprise information ...systems (EISs), to support and improve their decision-making processes. Since the ultimate goal of using EISs and Big Data analytics is the same, a logical task is to enable these systems to work together. In this paper we propose a framework of cooperation of these systems, based on the schema on read modeling approach and data virtualization. The goal of data virtualization process is to hide technical details related to data storage from applications and to display heterogeneous data sources as one integrated data source. We have tested the proposed model in a case study in the transportation domain. The study has shown that the proposed integration model responds flexibly and efficiently to the requirements related to adding new data sources, new data models and new data storage technologies.
PurposeAlthough much is understood about Business Intelligence (BI) technology adoption, less is known about the complementary organisational resources that drive the actual use of BI systems and the ...impacts of BI systems at an individual employee level. This study aims to develop and test a model of the impact of key complementary organisational resources on employees' actual BI systems’ use behaviours and their decision-making performance.Design/methodology/approachTo test the research model, a cross-sectional survey of 437 North American employees, who described themselves as using a BI system to make decisions, was conducted. The partial least square (PLS), a structural equational modelling (SEM) technique, was employed to analyse the survey data.FindingsThe survey findings attest to the influence of key complementary organisational resources (i.e. data-based culture (DBC), quality of data in source systems and decision-making autonomy) on employees' actual BI use (comprising BI system dependence and BI system infusion) and on their decision-making performance. Specifically, a DBC and the quality of data in source systems are found to significantly enhance BI system dependence and BI system infusion. Decision-making autonomy, DBC, BI system dependence and BI system infusion are significant contributors to achieving decision-making performance.Originality/valueThis study proposes a theoretical model of actual BI systems’ use from an individual user perspective that increases our understanding of both the complexity of BI usage and the complementary organisational resources that drive both actual BI systems’ use and the impacts of BI systems.
This paper designs business intelligence system for supply chain of herbal products in Indonesia. System design is done with system entity approach to obtain system attributes, conceptual system ...design using Businees Process Modeling Notation (BPMN) 2.0 and unified modeling language (UML) and finally integrated with pentaho business intelligence suite suite including integration and business analytics data. The result of business intelligence system design is able to transform raw data into information and mengintrpertasikannya in the form of a visual supply chain herbal products for the purposes of identification, development and create new business strategy opportunities.
The textile and apparel industry is one of the biggest competitive industries in the world. Nowadays, industry 4.0 concepts put pressures on textile and apparel companies to integrate advanced ...technologies. Consequently, Business Intelligence (BI) systems are diffusing rapidly to process large data sets to harness the true value of smart technologies. Regardless of its potentials, most textile and apparel companies are lagging and hesitating to adopt this credible innovation in the presence of a high failure rate (70%-80%) especially in developing countries. To achieve the successful adoption of BI systems, statistical assessment is required to better understand this complex phenomenon. Therefore, a BI system model based on Technology-Organization-Environment (TOE) is developed to evaluate the role of potential determinants pertaining to the users, technology, organization, and environment. Data were collected using a survey with self-administered questionnaires from decision-makers with authoritative designations in the textile and apparel industry, academia, and software companies. Influential relationships among critical determinants were assessed and validated by using Decision-Making Trial and Evaluation Laboratory (DEMATEL) approach. The results of this study would contribute to the success of costly BI system projects and will motivate the industry experts to potentially assign investments for the BI projects in the developing countries to sustain in the competitive markets.
ABSTRACT
Accounting information systems (AIS) capture and process accounting data and provide valuable information for decision makers. However, in a rapidly changing environment, continual ...management of the AIS is necessary for organizations to optimize performance outcomes. We suggest that building a dynamic AIS capability enables accounting process and organizational performance. Using the dynamic capabilities framework (Teece 2007) we propose that a dynamic AIS capability can be developed through the synergy of three competencies: having (1) a flexible AIS, (2) a complementary business intelligence system, and (3) accounting professionals with IT technical competency. Using survey data, we find evidence of a positive association between a dynamic AIS capability, accounting process performance, and overall firm performance. The results suggest that developing a dynamic AIS resource can add value to an organization. This study provides guidance for organizations looking to leverage the performance outcomes of their AIS environment.
Big data has become one of new research frontiers. It is a collection of a large-scale and complex data sets that it becomes more difficult to process using current database management systems and ...traditional data processing applications. There are two challenges while dealing with big data: (1) how to analyze big data efficiently; (2) visualization and presentation of big data because of the larger volume, variety, and velocity of the information. This study proposes a cloud business intelligence system for visual analytics with big data. A new kernel method for analyzing big data is proposed. The principle of semismooth support vector machine is introduced to collaborate with the interval regression model. The proposed kernel method can resolve the following problem efficiently: (1) big data; (2) noises and interaction of the separation margin; (3) unbalance of the separation margin.
In the last years, data warehousing has got attention from Universities which
are now adopting business intelligence solutions in order to analyze crucial
aspects of the academic context. In this ...paper, we present the architecture
of a Business Intelligence system for academic organizations. Then, we
illustrate the design process of the data warehouse devoted to the analysis
of the main factors affecting the importance and the quality level of every
University, such as the evaluation of the Research and the Didactics. The
design process we describe is based on a hybrid methodology that is largely
automatic and relies on an ontological approach for the integration of the
different data sources.
nema
La horticultura ornamental en México es una industria en crecimiento que requiere la inclusion de diversas tecnologias para automatizar la produccion y comercializacion a fin de incrementar su ...rentabilidad. Para esto, el analisis de los datos es clave, permitiendo la obtencion de conocimiento para el soporte a la toma de decisiones; no obstante, implica un tiempo exhaustivo de procesamiento de informacion, afectando la productividad de las empresas debido a la falta de un sistema de apoyo a la toma de decisiones que implemente herramientas dinamicas de inteligencia de negocios. Este trabajo de investigacion propone un sistema web de inteligencia de negocios para la creacion de herramientas dinamicas y ejecucion de consultas asincronas a la base de datos; lo cual, proporciona un analisis de la informacion historica de la comercializacion de plantas ornamentales mediante tablas, graficas y reportes. Esta desarrollado utilizando la metodologia PUA, el lenguaje de programacion Python y el framework Django, empleando un enfoque innovador al aplicar el algoritmo DFS como mecanismo de búsqueda para determinar la relacion existente entre las tablas de la base de datos, reduciendo tiempo de extraccion, procesamiento, analisis y presentacion de informacion. Como resultado se logro mejorar el aprovechamiento de la informacion historica, eficientar el procesamiento y analisis de la informacion de comercializacion y, por consiguiente, mejorar los procesos de toma de decisiones.
For decades, the marketing guidelines of enterprise software providers have focused on those managers who are likely to be more innovative in adopting new information systems. The current study ...argues that this approach demands improvements for two reasons: (1) this tactic may be biased, since past studies have only examined the single trait of innovativeness and its impact on an individual adoption intention and (2) the organisational implementation intention might be more important than the individual adoption intention, but the former has been largely ignored in the existing literature. Based on the case of business intelligence (BI) systems and data from 62 senior managers, this study is a pioneer in that it empirically reveals that managers' individual adoption intention is distinct from their organisational implementation intention. Further, while managers' innovativeness may be a significant determinant of their individual adoption intention towards BI systems, the issue of whether managers actually implement BI systems in their organisations is dominated by their involvement characteristics. Fruitful suggestions are proposed for practitioners and scholars.
PDF
