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  • 标题:Big Data and Analytics: Issues, Solutions, and ROI
  • 本地全文:下载
  • 作者:Shim, J. P. ; French, Aaron M. ; Guo, Chengqi
  • 期刊名称:Communications of the Association for Information Systems
  • 印刷版ISSN:1529-3181
  • 出版年度:2015
  • 卷号:37
  • 期号:1
  • 页码:39
  • 出版社:Association for Information Systems
  • 摘要:Recently, the topic of big data and analytics has received renewed attention from academia and practitioners. There has been an increase in demand for skills in big data and analytics due to the increasing speed, variety, and volume of information. Several research reports have shown that big data and analytics remain top priority for CIOs. A recent study shows how a company accurately predicted a teen girl’s pregnancy via the company’s big data algorithm. However, there are dark sides to big data and analytics. A panel discussion addressed topics concerning how companies ensure that big data projects clearly define measurable goals up front, methods that companies use to ensure maximum return and most effectively, and ways that companies evolve culture, processes, and technology to simultaneously maximize return. Most companies are looking at how they can effectively manage their business more through using their data assets. Companies today target an average return of $3.50 dollars for every dollar spent on big data projects. However, most are only returning a fraction of that today, which leaves room for improvement and the possibility that organizations will push back against new analytic technologies. In this paper, we cover these topics that a panel of researchers at AMCIS 2014 in Savannah, GA, discussed.
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