scholarly journals CF4BDA: A Conceptual Framework for Big Data Analytics Applications in the Cloud

IEEE Access ◽  
2015 ◽  
Vol 3 ◽  
pp. 1944-1952 ◽  
Author(s):  
Qinghua Lu ◽  
Zheng Li ◽  
Maria Kihl ◽  
Liming Zhu ◽  
Weishan Zhang
Keyword(s):  
Big Data ◽  
Conceptual Framework ◽  
Data Analytics ◽  
Big Data Analytics

scholarly journals Ambidextrous organization and agility in big data era

2018 ◽  
Vol 24 (5) ◽  
pp. 1091-1109 ◽  
Author(s):  
Riccardo Rialti ◽  
Giacomo Marzi ◽  
Mario Silic ◽  
Cristiano Ciappei
Keyword(s):  
Big Data ◽  
Conceptual Framework ◽  
Data Analytics ◽  
Design Methodology ◽  
Business Process Management ◽  
Process Management ◽  
Big Data Analytics ◽  
Organizational Agility ◽  
Content Type ◽  
Practical Implications

Purpose The purpose of this paper is to explore the effect of big data analytics-capable business process management systems (BDA-capable BPMS) on ambidextrous organizations’ agility. In particular, how the functionalities of BDA-capable BPMS may improve organizational dynamism and reactiveness to challenges of Big Data era will be explored. Design/methodology/approach A theoretical analysis of the potential of BDA-capable BPMS in increasing organizational agility, with particular attention to the ambidextrous organizations, has been performed. A conceptual framework was subsequently developed. Next, the proposed conceptual framework was applied in a real-world context. Findings The research proposes a framework highlighting the importance of BDA-capable BPMS in increasing ambidextrous organizations’ agility. Moreover, the authors apply the framework to the cases of consumer-goods companies that have included BDA in their processes management. Research limitations/implications The principal limitations are linked to the need to validate quantitatively the proposed framework. Practical implications The value of the proposed framework is related to its potential in helping managers to fully understand and exploit the potentiality of BDA-capable BPMS. Moreover, the implications show some guidelines to ease the implementation of such systems within ambidextrous organizations. Originality/value The research offers a model to interpret the effects of BDA-capable BPMS on ambidextrous organizations’ agility. In this way, the research addresses a significant gap by exploring the importance of information systems for ambidextrous organizations’ agility.

scholarly journals A Conceptual Framework For Measuring The Performance of Big Data Analytics Process

2017 ◽  
Vol 1 (2) ◽  
pp. 13-14 ◽  
Author(s):  
Ismail Mohamed Ali ◽  
Yusmadi Yah Jusoh ◽  
Rusli Abdullah ◽  
Rozi Nor Haizan Nor ◽  
Hairulnizam Mahdin
Keyword(s):  
Big Data ◽  
Conceptual Framework ◽  
Data Analytics ◽  
Big Data Analytics

scholarly journals Advancing manufacturing systems with big-data analytics: A conceptual framework

2020 ◽  
Vol 33 (2) ◽  
pp. 169-188 ◽  
Author(s):  
Dominik Kozjek ◽  
Rok Vrabič ◽  
Borut Rihtaršič ◽  
Nada Lavrač ◽  
Peter Butala
Keyword(s):  
Big Data ◽  
Conceptual Framework ◽  
Data Analytics ◽  
Manufacturing Systems ◽  
Big Data Analytics

scholarly journals A conceptual framework for the adoption of big data analytics by e-commerce startups: a case-based approach

2019 ◽  
Vol 17 (2-4) ◽  
pp. 285-318 ◽  
Author(s):  
Abhishek Behl ◽  
Pankaj Dutta ◽  
Stefan Lessmann ◽  
Yogesh K. Dwivedi ◽  
Samarjit Kar
Keyword(s):  
Big Data ◽  
Conceptual Framework ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Case Based

scholarly journals Business Intelligence and Big Data Analytics for Organizational Performance Management in Public Sector: The Conceptual Framework

2016 ◽  
Vol 22 (8) ◽  
pp. 1919-1923
Author(s):  
Jamaiah H Yahaya ◽  
Aziz Deraman ◽  
Nor Hani Zulkifli Abai ◽  
Zulkefli Mansor ◽  
Yusmadi Yah Jusoh
Keyword(s):  
Big Data ◽  
Public Sector ◽  
Conceptual Framework ◽  
Organizational Performance ◽  
Performance Management ◽  
Business Intelligence ◽  
Data Analytics ◽  
Big Data Analytics

Big Data Analytics: Opportunity or Threat for the Accounting Profession?

2017 ◽  
Vol 31 (3) ◽  
pp. 63-79 ◽  
Author(s):  
Greg Richins ◽  
Andrea Stapleton ◽  
Theophanis C. Stratopoulos ◽  
Christopher Wong
Keyword(s):  
Big Data ◽  
Conceptual Framework ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Structured Data ◽  
Exploratory Analysis ◽  
Unstructured Data ◽  
Accounting Profession ◽  
Leading Role

ABSTRACT Contrary to Frey and Osborne's (2013) prediction that the accounting profession faces extinction, we argue that accountants can still create value in a world of Big Data analytics. To advance this position, we provide a conceptual framework based on structured/unstructured data and problem-driven/exploratory analysis. We argue that accountants already excel at problem-driven analysis of structured data, are well positioned to play a leading role in the problem-driven analysis of unstructured data, and can support data scientists performing exploratory analysis on Big Data. Our argument rests on two pillars: accountants are familiar with structured datasets, easing the transition to working with unstructured data, and possess knowledge of business fundamentals. Thus, rather than replacing accountants, we argue that Big Data analytics complements accountants' skills and knowledge. However, educators, standard setters, and professional bodies must adjust their curricula, standards, and frameworks to accommodate the challenges of Big Data analytics.

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