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  • 标题:Studi On Big Data Analytics Framework in Smart City Context
  • 本地全文:下载
  • 作者:Rahmawati Dinda ; Arief Assaf ; Do Abdullah Saiful Saiful
  • 期刊名称:E3S Web of Conferences
  • 印刷版ISSN:2267-1242
  • 电子版ISSN:2267-1242
  • 出版年度:2021
  • 卷号:328
  • 页码:1-4
  • DOI:10.1051/e3sconf/202132804022
  • 语种:English
  • 出版社:EDP Sciences
  • 摘要:The issue of global urbanization, which is a separate problem faced by the government, is the very rapid growth of population density in cities. To face this challenge, the government launched a smart city project by targeting sustainable economic growth and improving the quality of life. Information and Communication Technology governance is the key to realizing a smart city. However, each of these I.C.T. tools produce large amounts of data known as Big Data. Data processing with the Big Data approach is becoming a trend in information systems to provide better public services and provide references in the policy-making process. However, to obtain important information in the scope of big data, a Big Data Analytics process is needed, also known as Big Data Value Chain. Extracting knowledge from the related literature can identify the characteristics of the big data analytic framework for smart cities. This paper reviews several big data analytic frameworks applied to smart cities. This paper is to find the advantages and disadvantages of each framework so that it can be a direction for future research.
  • 关键词:Big Data Analytic;Framework;Smart City;Big Data Value Chain
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