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1.
Big data analytics and business analytics are a disruptive technology and innovative solution for enterprise development. However, what is the relationship between business analytics, big data analytics, and enterprise information systems (EIS)? How can business analytics enhance the development of EIS? How can analytics be incorporated into EIS? These are still big issues. This article addresses these three issues by proposing ontology of business analytics, presenting an analytics service-oriented architecture (ASOA) and applying ASOA to EIS, where our surveyed data analysis showed that the proposed ASOA is viable for developing EIS. This article then examines incorporation of business analytics into EIS through proposing a model for business analytics service-based EIS, or ASEIS for short. The proposed approach in this article might facilitate the research and development of EIS, business analytics, big data analytics, and business intelligence.  相似文献   

2.
While many studies on big data analytics describe the data deluge and potential applications for such analytics, the required skill set for dealing with big data has not yet been studied empirically. The difference between big data (BD) and traditional business intelligence (BI) is also heavily discussed among practitioners and scholars. We conduct a latent semantic analysis (LSA) on job advertisements harvested from the online employment platform monster.com to extract information about the knowledge and skill requirements for BD and BI professionals. By analyzing and interpreting the statistical results of the LSA, we develop a competency taxonomy for big data and business intelligence. Our major findings are that (1) business knowledge is as important as technical skills for working successfully on BI and BD initiatives; (2) BI competency is characterized by skills related to commercial products of large software vendors, whereas BD jobs ask for strong software development and statistical skills; (3) the demand for BI competencies is still far bigger than the demand for BD competencies; and (4) BD initiatives are currently much more human-capital-intensive than BI projects are. Our findings can guide individual professionals, organizations, and academic institutions in assessing and advancing their BD and BI competencies.  相似文献   

3.
The Big Data era has descended on many communities, from governments and e-commerce to health organizations. Information systems designers face great opportunities and challenges in developing a holistic big data research approach for the new analytics savvy generation. In addition business intelligence is largely utilized in the business community and thus can leverage the opportunities from the abundant data and domain-specific analytics in many critical areas. The aim of this paper is to assess the relevance of these trends in the current business context through evidence-based documentation of current and emerging applications as well as their wider business implications. In this paper, we use BigML to examine how the two social information channels (i.e., friends-based opinion leaders-based social information) influence consumer purchase decisions on social commerce sites. We undertake an empirical study in which we integrate a framework and a theoretical model for big data analysis. We conduct an empirical study to demonstrate that big data analytics can be successfully combined with a theoretical model to produce more robust and effective consumer purchase decisions. The results offer important and interesting insights into IS research and practice.  相似文献   

4.
Although big data analytics have been widely considered a key driver of marketing and innovation processes, whether and how big data analytics create business value has not been fully understood and empirically validated at a large scale. Taking social media analytics as an example, this paper is among the first attempts to theoretically explain and empirically test the market performance impact of big data analytics. Drawing on the systems theory, we explain how and why social media analytics create super-additive value through the synergies in functional complementarity between social media diversity for gathering big data from diverse social media channels and big data analytics for analyzing the gathered big data. Furthermore, we deepen our theorizing by considering the difference between small and medium enterprises (SMEs) and large firms in the required integration effort that enables the synergies of social media diversity and big data analytics. In line with this theorizing, we empirically test the synergistic effect of social media diversity and big data analytics by using a recent large-scale survey data set from 18,816 firms in Italy. We find that social media diversity and big data analytics have a positive interaction effect on market performance, which is more salient for SMEs than for large firms.  相似文献   

5.
操作型商业智能综述   总被引:3,自引:0,他引:3  
为了为日常工作提供商业智能支持,研究了商业智能自身在发展过程中概念的转变,以及近年商业智能针对企业不同应用层次产生的新分类.研究了操作型商业智能的定义与定位,根据商业智能的通用架构和操作型商业智能的特点提出了通用的操作型商业智能系统的架构.对操作型商业智能组成模块的技术现状进行研究,分别研究了操作型商业智能与企业业务流程融合以及数据加载问题,重点对加快数据加载速度的技术进行了总结与归纳,结果表明了架构在技术上的可行性.  相似文献   

6.
为解决大量数据无法快速进行可视化分析挖掘的问题,江苏核电基于开源技术进行定制化开发,按照层次化功能架构设计,对平台的数据层、逻辑层和展示层的功能进行开发,快速构建大数据可视化平台,有效解决对数据进行可视化分析的问题。文章从功能特点、建设要求、经济性等维度对大数据可视化产品和传统商务智能产品进行对比,阐述建设可视化分析平台的优点和必要性;梳理与建立基于平台的数据可视化分析的服务的管理流程和职责分工,平台成果应用于物资编码检查分析与可视化业务看板等方面,在支撑管理决策、提升管理水平、提高业务运营效率和改进优化业务四个方面体现了平台的价值。文章介绍的大数据可视化分析平台的建设思路和方法可有效提升数据分析的工作效率。  相似文献   

7.
Recent advances in information technology (IT), such as the advent of business intelligence (BI) systems, have increased the ability of organisations to collect and analyse data to support decisions. There is little focus to date, however, on how BI systems might play a role in organisational knowledge creation – in organisational knowing. We develop a conceptual framework of organisational knowing based on a synthesis of the literature, and use this as a framework to investigate how BI systems facilitate knowing in a case organisation. We identify two practices triggered by BI systems that distinguish them from prior applications of IT: the ability to initiate problem articulation and dialogue, and that of data selection (e.g. to address information needs of organisational decision makers at different managerial levels). This study provides empirical evidence of the performative outcome of BI systems in relation to organisational knowing through the practices of articulation and data selection. It provides a practice perspective on BI and focuses on the role of BI systems in organisational knowing thereby opening up a new departure for BI research that considers the implications of BI systems in organisations with actual practice in mind.  相似文献   

8.
The emergence of big data analytics (BDA) has posed opportunities as well as multiple challenges to business practitioners, who have called for research on the behavioural factors underlying BDA adoption at the individual level. The purpose of this study is to extend the information systems (IS) research on storytelling and to explore the role and characteristics of deliberate storytelling in individual‐level BDA adoption. This case study used the grounded theory approach to extract qualitative data from 24 interviews, field notes, and documentary data. The explicit contributions of the study to the literature include (a) increasing our understanding of the facilitating role of deliberate storytelling in individual‐level BDA adoption, (b) identifying four deliberate storytelling patterns and seven underlying corporate stories disseminated by organizations to influence individual behaviour, and (c) defining the core characteristics of effective deliberate storytelling. This study has multiple implications for business practitioners and demonstrates how deliberate storytelling can be used as a facilitating mechanism in daily business practice.  相似文献   

9.
对XML/A协议的应用进行了探讨,并且利用XML/A协议作为底层,结合Web Service实现了Web智能应用程序,方便用户进行在线分析和数据挖掘,达到了客户端的平台无关性目标,在信息系统的扩展方面做了很好的探索。  相似文献   

10.
This paper examines external pressures that influence the relationship between an organization's business intelligence (BI) data collection strategy and the purpose for which BI is implemented. A model is proposed and tested that is grounded in institutional theory, research about competitive pressure, and research about the purpose of BI. Two data collection strategies (comprehensive and problem driven) and three BI purposes (insight, consistency, and transformation) are examined. 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.  相似文献   

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