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Open AccessJournal ArticleDOI

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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Journal ArticleDOI

Finding the four qualities of intelligent industrial reporting

TL;DR: This paper identifies four qualities for the practical application of data analytics, with the aim of intelligent reporting, which are focus area, data availability, analytics, and visualisation.
Book ChapterDOI

Phase III: CSDS Gap-Prescriptions—Design Science Problem-Solving

TL;DR: In this paper, the final phase frames and advocates design-derived gap-prescriptions, which is a natural accompaniment to conclude diagnostic analysis in problem-solving research, as suggested by Doorewaard and Verschuren (2010).
Posted ContentDOI

Prediction Modeling of Mental Well-Being Using Health Behavior Data of College Students

TL;DR: The top five most salient features associated with predicting poor mental well-being include body mass index, number of sports activities per week, grade point average (GPA), sedentary hours, and age.
Journal ArticleDOI

How can Big Data contribute to improve the financial performance of companies

TL;DR: In this paper, the authors proposed a comprehensive methodology that combines a set of Big Data Analytics tools (BDA) with prospective analysis, risk analysis and strategic analysis with the aim to improve the firm's financial performance measured through Key Performance Indicators (KPIs).
Journal ArticleDOI

Empowering Data Mining Sciences by Habitual Domains Theory, Part I: The Concept of Wonderful Solution

TL;DR: A general formal model for decision-making and new knowledge generation that can be used in post-data mining analysis to derive better decisions and can also be used to empower other sciences such as political sciences, medical sciences, management sciences and research activities in all areas.
References
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Posted Content

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.
Journal ArticleDOI

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.
Journal ArticleDOI

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.
Journal ArticleDOI

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.
Journal ArticleDOI

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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