Big Data Analytic Framework for Organizational Leverage

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Date
2021-03-06
Open Access Location
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Publisher
MDPI (Basel, Switzerland)
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The Author(s) CC BY 4.0
Abstract
Web data have grown exponentially to reach zettabyte scales. Mountains of data come from several online applications, such as e-commerce, social media, web and sensor-based devices, business web sites, and other information types posted by users. Big data analytics (BDA) can help to derive new insights from this huge and fast-growing data source. The core advantage of BDA technology is in its ability to mine these data and provide information on underlying trends. BDA, however, faces innate difficulty in optimizing the process and capabilities that require merging of diverse data assets to generate viable information. This paper explores the BDA process and capabilities in leveraging data via three case studies who are prime users of BDA tools. Findings emphasize four key components of the BDA process framework: system coordination, data sourcing, big data application service, and end users. Further building blocks are data security, privacy, and management that represent services for providing functionality to the four components of the BDA process across information and technology value chains.
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Keywords
big data, big data analytics, big data process, big data analytic framework
Citation
APPLIED SCIENCES-BASEL, 2021, 11 (5)
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