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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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Job schedulers for Big data processing in Hadoop environment: testing real-life schedulers using benchmark programs

TL;DR: An overview of big data is given and the advantages, disadvantages, features, and drawbacks of various Hadoop job schedulers such as FIFO, Fair, capacity, Deadline Constraints, Delay, LATE, Resource Aware, etc, are described and a comparative study among these Schedulers is provided.
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Using Tableau to visualize data and drive decision-making

TL;DR: This case emphasizes the importance of data analysis through the usage of data visualization software to help you gain an understanding of data and how it can be transformed into information that can enhance the decision-making process.
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Big data analytics (BDA) and degree of internationalization: the interplay between governance of BDA infrastructure and BDA capabilities

TL;DR: In this article, a quantitative analysis based on an Ordinary Least Squares (OLS) regression showed that the relationship between governance of big data analytics infrastructure and the degree of internationalization is not significant, while the direct effect of BDA capabilities as well as the interaction term between BDA infrastructure and big data capabilities are positive and significant.
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Big data and its strategic path to value in international firms

TL;DR: In this article, the authors explore the impact of big data usage on firms' strategic orientations and their implications on business performance, and provide theoretical and practical reflections on the use of BD in firms' strategies.
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A New Methodological Frontier in Entrepreneurship Research: Big Data Studies:

TL;DR: The emergence of big data and related analytic techniques are creating opportunities to advance empirical entrepreneurship theory and practice as discussed by the authors, focusing on the implications for the implications of the big data for the future of entrepreneurship.
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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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