Design of Data Classification and Classification Management System for Big Data of Hydropower Enterprises Based on Data Standards

Wei Luo, Jian Xu, Ziqi Zhou
{"title":"Design of Data Classification and Classification Management System for Big Data of Hydropower Enterprises Based on Data Standards","authors":"Wei Luo, Jian Xu, Ziqi Zhou","doi":"10.1155/2022/8103897","DOIUrl":null,"url":null,"abstract":"The advent of the era of big data has had a great impact on traditional management methods, and companies have also begun to make changes. The management approach has changed from initially focusing on business development to now focusing on user experience and putting people first. The data standard classification management system is a system for management and analysis based on the database. Therefore, this article is based on data standards, taking hydropower companies as an example, to design and research the data classification management system to promote the operation and safety of hydropower companies. This article mainly uses the experimental method, data collection method, and algorithm analysis method to thoroughly understand and explore the content of this article. The experimental results show that the testability of this article can basically reach the general level, and the delay time of the system does not exceed 10 seconds, which can be applied to the company.","PeriodicalId":18790,"journal":{"name":"Mob. Inf. Syst.","volume":"38 1","pages":"8103897:1-8103897:7"},"PeriodicalIF":0.0000,"publicationDate":"2022-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Mob. Inf. Syst.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1155/2022/8103897","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

Abstract

The advent of the era of big data has had a great impact on traditional management methods, and companies have also begun to make changes. The management approach has changed from initially focusing on business development to now focusing on user experience and putting people first. The data standard classification management system is a system for management and analysis based on the database. Therefore, this article is based on data standards, taking hydropower companies as an example, to design and research the data classification management system to promote the operation and safety of hydropower companies. This article mainly uses the experimental method, data collection method, and algorithm analysis method to thoroughly understand and explore the content of this article. The experimental results show that the testability of this article can basically reach the general level, and the delay time of the system does not exceed 10 seconds, which can be applied to the company.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于数据标准的水电企业大数据数据分类与分类管理系统设计
大数据时代的到来对传统的管理方式产生了很大的冲击,企业也开始进行变革。管理方法已经从最初的关注业务发展转变为现在的关注用户体验和以人为本。数据标准分类管理系统是一个基于数据库的管理和分析系统。因此,本文以数据标准为基础,以水电公司为例,对数据分类管理系统进行设计和研究,以促进水电公司的运行和安全。本文主要采用实验法、数据收集法和算法分析法对本文的内容进行深入的理解和探讨。实验结果表明,本文的可测试性基本可以达到一般水平,系统的延迟时间不超过10秒,可以应用于公司。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Cardinality estimation via learned dynamic sample selection Flexible temporal constraint management in modularized processes Efficient query evaluation techniques over large amount of distributed linked data Event-Case Correlation for Process Mining using Probabilistic Optimization Feature Extraction of Foul Action of Football Players Based on Machine Vision
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1