...
首页> 外文期刊>Artificial Intelligence Review: An International Science and Engineering Journal >The state of the art and taxonomy of big data analytics: view from new big data framework
【24h】

The state of the art and taxonomy of big data analytics: view from new big data framework

机译:大数据分析的艺术状态和分类:来自新大数据框架的视图

获取原文
获取原文并翻译 | 示例
           

摘要

Big data has become a significant research area due to the birth of enormous data generated from various sources like social media, internet of things and multimedia applications. Big data has played critical role in many decision makings and forecasting domains such as recommendation systems, business analysis, healthcare, web display advertising, clinicians, transportation, fraud detection and tourism marketing. The rapid development of various big data tools such as Hadoop, Storm, Spark, Flink, Kafka and Pig in research and industrial communities has allowed the huge number of data to be distributed, communicated and processed. Big data applications use big data analytics techniques to efficiently analyze large amounts of data. However, choosing the suitable big data tools based on batch and stream data processing and analytics techniques for development a big data system are difficult due to the challenges in processing and applying big data. Practitioners and researchers who are developing big data systems have inadequate information about the current technology and requirement concerning the big data platform. Hence, the strengths and weaknesses of big data technologies and effective solutions for Big Data challenges are needed to be discussed. Hence, due to that, this paper presents a review of the literature that analyzes the use of big data tools and big data analytics techniques in areas like health and medical care, social networking and internet, government and public sector, natural resource management, economic and business sector. The goals of this paper are to (1) understand the trend of big data-related research and current frames of big data technologies; (2) identify trends in the use or research of big data tools based on batch and stream processing and big data analytics techniques; (3) assist and provide new researchers and practitioners to place new research activity in this domain appropriately. The findings of this study will provide insights and knowledge on the existing big data platforms and their application domains, the advantages and disadvantages of big data tools, big data analytics techniques and their use, and new research opportunities in future development of big data systems.
机译:由于来自社交媒体,物联网和多媒体应用等各种来源产生的巨大数据,大数据已成为一个重要的研究领域。大数据在许多决策制作和预​​测领域中发挥着关键作用,如推荐系统,业务分析,医疗保健,网络展示广告,临床医生,运输,欺诈检测和旅游营销。在研究和工业社区中的Hadoop,Storm,Spark,Flink,Kafka和猪等各种大数据工具的快速发展允许分发,传达和处理的大量数据。大数据应用使用大数据分析技术来有效地分析大量数据。然而,由于处理和应用大数据的挑战,根据批量和流数据处理和开发的分析技术选择基于批量和流数据处理和分析技术的分析技术很困难。正在开发大数据系统的从业者和研究人员具有关于当前技术和关于大数据平台的要求的信息不足。因此,需要讨论大数据技术和大数据挑战的有效解决方案的优势和缺点。因此,本文提出了对卫生和医疗,社交网络,互联网,政府和公共部门,自然资源管理,自然资源管理,自然资源管理,自然资源管理,自然资源管理,自然资源管理,自然资源管理,经济和商业部门。本文的目标是(1)了解大数据技术的大数据相关研究和当前帧的趋势; (2)根据批量和流处理和大数据分析技术确定使用或研究大数据工具的趋势; (3)协助并提供新的研究人员和从业者,以适当地在这个领域中进行新的研究活动。本研究的调查结果将为现有的大数据平台及其应用领域提供洞察和知识,大数据工具的优缺点,大数据分析技术及其使用以及未来大数据系统的发展中的新研究机会。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号