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面向工业领域的数据湖架构研究

Research on data lake architecture for industrial field
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摘要 制造企业在数字化转型中的核心任务之一是建立工业数据体系并有效管理数据。然而,在智能化转型过程中,许多企业都面临“工业数据孤岛”的问题。数据湖架构提供了解决这一问题的方案。文章旨在分析制造企业数字化转型的背景下,工业大数据的内涵、典型特征以及现状,探讨数据湖架构在工业领域的应用,以为实现制造业数字化改造和智能化升级提供数据支持。 One of the core tasks for manufacturing enterprises in digital transformation is to establish an industrial data system and effectively manage data.However,in the process of intelligent transformation,many enterprises are facing the problem of“industrial data silos”.The data lake architecture provides a solution to this problem.The article aims to analyze the connotation,typical characteristics,and current situation of industrial big data in the context of digital transformation of manufacturing enterprises,explore the application of data lake architecture in the industrial field,and provide data support for achieving digital transformation and intelligent upgrading of manufacturing industry.
作者 李剑 LI Jian(Beijing University of Civil Engineering and Architecture,Beijing 102627,China)
机构地区 北京建筑大学
出处 《计算机应用文摘》 2024年第3期104-106,共3页 Chinese Journal of Computer Application
关键词 智能制造 工业大数据 数据湖 数据仓库 intelligent manufacturing industrial big data data lake data warehouse
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  • 1Wu X D, Zhu X Q, Wu G Q, Ding W. Data mining with big data. IEEE Transactions on Knowledge and Data Engi- neering, 2014, 26(1): 97-107.
  • 2Syed A R, Gillela K, Venugopal C. The future revolution on big data. International Journal of Advanced Research in Computer and Communication Engineering, 2013, 2(6): 2446-2451.
  • 3Condliffe J. The problem with big data is that nobody und- erstands it [Online], available: http://gizmodo.com/59062- 04/the-problem-wit h-big-dat a-is-t hat- nobody-understan- ds-it, April 30, 2012.
  • 4Manyika J, Chui M, Brown B, Bughin J, Dobbs R, Roxburgh C, Byers A H. Big data: the next frontier for innovation, competition, and productivity. McKinsey Global Institute Report [Online], available: http://www.mckinsey.com/insig hts/mgi/research/technology_and_innovation/big_data_the_ next_frontier_for_innovation, June, 2011.
  • 5Halevi G, Moed H. The Evolution of big data as a research and scientific topic: overview of the literature. Special Issue on Big Data, Research Trends, 2012, (30): 1-37.
  • 6Ginsberg J, Mohebbi M H, Patel R S, Brammer L, Smolinski M S, Brilliant L. Detecting influenza epidemics using search engine query data. Nature, 2009, 457(7232): 1012-1014.
  • 7Preis T, Moat H S, Stanley H E. Quantifying trading be- havior in financial markets using Google trends. Scientific Reports, 2013, 3:1684.
  • 8钟路音.工业数据增速是其他大数据领域的两倍.人民邮电报.
  • 9Industrial Big Data. Know the future-automate processes. Software for data analysis and accurate forecasting IOn- line], available: http://differentia.co/qlikview/docs/Blue- Yonder-White-Paper-Industrial-Big-Data.pdf, October 23, 2015.
  • 10Obitko M, Jirkovsk: V, Bezdfek J. Big data challenges in industrial automation. Industrial Applications of Holonic and Multi-Agent Systems, Lecture Notes in Computer Sci- ence. Berlin Heidelberg: Springer, 2013, 8062:305-316.

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