- DOI: 10.1108/intr-04-2021-0231
- Corpus ID: 249214999
Exploring core knowledge in business intelligence research
- Wen-Lung Shiau , Hao Chen , +1 author Yogesh Kumar Dwivedi
- Published in Internet Research 31 May 2022
- Business, Computer Science
5 Citations
The role of big data analytics and organizational agility in improving organizational performance of business processing organizations, problem resolution with business analytics: a task-technology fit perspective, developing a digital transformation architecture framework: a business intelligence approach, big data in relation with business intelligence capabilities and e-commerce during covid-19 pandemic in accountant’s perspective, the precursors of ai adoption in business: towards an efficient decision-making and functional performance, 95 references, research landscape of business intelligence and big data analytics: a bibliometrics study, business intelligence and analytics: from big data to big impact, big data analytics and firm performance: effects of dynamic capabilities, getting value from business intelligence systems: a review and research agenda, towards business intelligence systems success: effects of maturity and culture on analytical decision making, transforming decision-making processes: a research agenda for understanding the impact of business analytics on organisations, advanced analytics: opportunities and challenges, integrated understanding of big data, big data analysis, and business intelligence: a case study of logistics, measuring the effects of business intelligence systems: the relationship between business process and organizational performance, the impact model of business intelligence on decision support and organizational benefits, related papers.
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BUSINESS INTELLIGENCE AND ANALYTICS: FROM BIG DATA TO BIG IMPACT
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IJSES Editor
The paradigm of Big Data has been established as a solid field of studies in many areas such as healthcare, science, transport, education, government services, among others. Despite widely discussed, there is no agreed definition about the paradigm although there are many concepts proposed by the academy and industry. This work aims to provide an analytical view of the studies conducted and published regarding the Big Data paradigm. The approach used is the systematic map of the literature, combining bibliometric analysis and content analysis to depict the panorama of research works, identifying patterns, trends, and gaps. The results indicate that there is still a long way to go, both in research and in concepts, such as building and defining adequate infrastructures and standards, to meet future challenges and for the paradigm to become effective and bring the expected benefits.
Amine Aziza
Anja Lorenz
Tamaro Green
This prospectus proposes research in emerging technologies in big data in education and how they can be applied to increasing the value of data to the organization. Some of the technologies reviewed are big data ecosystems, data mining methods and algorithms. This prospectus outlines the research of big data systems, data analysis, data mining, and decision making in education.
Jaydip Sen , Sanjib Biswas
Advancement in information and communication technology (ICT) has given rise to explosion of data in every field of operations. Working with the enormous volume of data (or Big Data, as it is popularly known as) for extraction of useful information to support decision making is one of the sources of competitive advantage for organizations today. Enterprises are leveraging the power of analytics in formulating business strategy in every facet of their operations to mitigate business risk. Volatile global market scenario has compelled the organizations to redefine their supply chain management (SCM). In this paper, we have delineated the relevance of Big Data and its importance in managing end to end supply chains for achieving business excellence. A Big Data-centric architecture for SCM has been proposed that exploits the current state of the art technology of data management, analytics and visualization. The security and privacy requirements of a Big Data system have also been highlighted and several mechanisms have been discussed to implement these features in a real world Big Data system deployment in the context of SCM. Some future scope of work has also been pointed out.
DR.C.KARTHIKEYAN DR.C.KARTHIKEYAN
Journal of Enterprise Information Management
Chris Kimble
Purpose – Data from social media (SM) has grown exponentially and created new opportunities for businesses to supplement their business intelligence (BI). However, there are many different platforms all of which are in a constant state of evolution. The purpose of this paper is to describe a generic methodology for the gathering of data from SM and transforming it into valuable BI. Design/methodology/approach – The approach taken is termed virtual excavation and builds on the similarities between the manipulation of technological artefacts virtual communities using various forms of SM and the excavation and analysis of physical artefacts found in archaeological settlements. Findings – The paper reports on a case study using this technique that looks at the Facebook fan pages of three mobile telecommunications service providers in Greece. The paper identifies many of the standard BI indicators as well as demonstrating that additional information relating to cross-page use can be collected by looking at how users manipulate artefact such as the “like” button in Facebook. Research limitations/implications – Although the methodology is widely applicable, the paper only reports on the analysis of one platform, Facebook, and is heavily reliant on visualization tools. Future work will examine different platforms and different tools for analysis. Practical implications – The paper discusses some of the ways in which this approach could be used and suggests some areas in which it might be applied. Originality/value – The approach of using virtual excavations to extract BI from virtual communities in online SM offers a systematic approach for dealing with a variety of information from a variety of different media that is not found in techniques based on information systems or management science.
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