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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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Measuring the perceived benefits of implementing blockchain technology in the banking sector

TL;DR: The developed instrument could help give decision makers a foundational view to measure the benefits of implementing blockchain technology before they choose to integrate it in their existing system.
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Deep Learning for Network Traffic Monitoring and Analysis (NTMA): A Survey

TL;DR: In this paper, a comprehensive review on applications of deep learning in network traffic monitoring and analysis (NTMA) applications is provided, where the authors discuss key challenges, open issues, and future research directions for using deep learning for NTMA applications.
Posted Content

Natural Language Processing Advancements By Deep Learning: A Survey

TL;DR: This survey categorizes and addresses the different aspects and applications of NLP that have benefited from deep learning and describes how deep learning methods and models advance these areas.
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Unlocking the drivers of big data analytics value in firms

TL;DR: An empirically validated model supported by a survey conducted on 175 European firms to explain the antecedents of BDA sustained value is proposed and provides directions for managers to support their decisions on BDA strategy definition and refinement.
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Factors influencing effective use of big data: A research framework

TL;DR: This paper casts a wide net to understand and consolidate from literature the potential factors that can influence the effective use of big data, so they may be further studied.
References
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Towards a Methodology for Developing Evidence-Informed Management Knowledge by Means of Systematic Review

TL;DR: The extent to which the process of systematic review can be applied to the management field in order to produce a reliable knowledge stock and enhanced practice by developing context-sensitive research is evaluated.
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Towards a Methodology for Developing Evidence-Informed Management Knowledge by Means of Systematic Review

TL;DR: In this article, the authors evaluate the process of systematic review used in the medical sciences to produce a reliable knowledge stock and enhanced practice by developing context-sensitive research and highlight the challenges in developing an appropriate methodology.
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Business intelligence and analytics: from big data to big impact

TL;DR: This introduction to the MIS Quarterly Special Issue on Business Intelligence Research first provides a framework that identifies the evolution, applications, and emerging research areas of BI&A, and introduces and characterized the six articles that comprise this special issue in terms of the proposed BI &A research framework.
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Critical questions for big data

TL;DR: The era of Big Data has begun as discussed by the authors, where diverse groups argue about the potential benefits and costs of analyzing genetic sequences, social media interactions, health records, phone logs, government records, and other digital traces left by people.
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Beyond the hype

TL;DR: The need to develop appropriate and efficient analytical methods to leverage massive volumes of heterogeneous data in unstructured text, audio, and video formats is highlighted and the need to devise new tools for predictive analytics for structured big data is reinforced.
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