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Critical analysis of Big Data challenges and analytical methods

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TLDR
In this article, the authors present a state-of-the-art review that presents a holistic view of the BD challenges and BDA methods theorized/proposed/employed by organizations to help others understand this landscape with the objective of making robust investment decisions.
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This article is published in Journal of Business Research.The article was published on 2017-01-01 and is currently open access. It has received 1267 citations till now. The article focuses on the topics: Analytics & Big data.

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Green innovation and organizational performance: The influence of big data and the moderating role of management commitment and HR practices

TL;DR: In this article, the authors developed and tested a holistic model that depicts and examines the relationships among green innovation, its drivers, as well as factors that help overcome the technological challenges and influence the performance and competitive advantage of the firm.
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A survey towards an integration of big data analytics to big insights for value-creation

TL;DR: This article presents a comprehensive, well-informed examination, and realistic analysis of deploying big data analytics successfully in companies and presents a methodical analysis for the usage of Big Data Analytics in various applications such as agriculture, healthcare, cyber security, and smart city.
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Artificial intelligence and business models in the sustainable development goals perspective: A systematic literature review

TL;DR: In this article, the authors investigated the role of Artificial Intelligence (AI) in the construction of sustainable business models (SBMs) and provided a quantitative overview of the academic literature that constitutes the field.
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Big data analytics as an operational excellence approach to enhance sustainable supply chain performance

TL;DR: In this paper, the authors used dynamic capability theory as a foundation for evaluating the role of BDA capability as an operational excellence approach in improving sustainable supply chain performance, and identified two pathways that managers can use to improve sustainable supply-chain outcomes in the mining industry based on big data analytics capabilities.
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Role of institutional pressures and resources in the adoption of big data analytics powered artificial intelligence, sustainable manufacturing practices and circular economy capabilities

TL;DR: In this article, the authors employed institutional theory and resource-based view theory to elucidate the way in which automotive firms configure tangible resources and workforce skills to drive technological enablement and improve sustainable manufacturing practices and furthermore develop circular economy capabilities.
References
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Journal ArticleDOI

Task scheduling for MapReduce in heterogeneous networks

TL;DR: In this paper, the task scheduling in MapReduce is considered for geo-distributed data centers on heterogeneous networks, and the proposed algorithms outperform the current existing ones and have better performance than those with random task-sequences.
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Big data analytics: The case of the social security administration

TL;DR: In this paper, the authors analyze various efforts undertaken by the United States Social Security Administration (SSA) in the domain of big data analytics, and discuss policy implications and explore issues to consider when public agencies begin to develop their capacity to analyze big data.
Journal ArticleDOI

A Systematic Review on the Profiling of Digital News Portal for Big Data Veracity

TL;DR: This paper provides a complete review of literature related to profiling digital news portal in data veracity and describes the structure of research topics, research trends with publications and framework veracity model validated.
Proceedings ArticleDOI

Software analytics to software practice: a systematic literature review

TL;DR: A systematic literature review of SA research has shown that much of the available SA research only serves the needs of developers, and there is plenty of room for future research in the SA field.
Journal ArticleDOI

Tuning small analytics on Big Data

TL;DR: This paper studies the feasibility of solving OLAP queries with Hadoop (the Apache project implementing MapReduce) while benefiting from secondary indexes and partitioning in HBase and the comparison of different access plans and the definition of criteria to choose among them in terms of consumed resources.
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