多站点企业高级数据分析的问题与挑战

Helena Dudycz, P. Stefaniak, Pawel Pyda
{"title":"多站点企业高级数据分析的问题与挑战","authors":"Helena Dudycz, P. Stefaniak, Pawel Pyda","doi":"10.1142/S2196888822500063","DOIUrl":null,"url":null,"abstract":"The new generation of industry, i.e. Industry 4.0, pertains to the processing of immense amounts of data, resulting, among other things, from the large-scale use of microcontrollers to control machines, an increase in the scale of automation, the use of the Internet of Things technology — e.g. in sensors installed at different stages of the production process, the implementation of the digital twin concept, and many other technologies designed to collect data (e.g. GPS or RFID). These data are collected in the enterprise’s variety of resources and databases. These data can be a valuable source of information and knowledge if the right approach to advanced data analysis is adopted, which depends, among other things, on the enterprise’s existing IT infrastructure. This paper sets out to present conclusions formulated on the basis of research consisting in the analysis of multinational manufacturing companies’ existing IT infrastructures. Three basic model solutions of IT architecture occurring in multi-site enterprises were identified, which made it possible to identify the main problems stemming from the IT architecture in place and concerning the analysis of data for the needs of company management. Additionally, this paper discusses the challenges faced by multi-site manufacturing companies. One such activity is the modification and expansion of the company’s IT infrastructure, including the implementation of Big Data and Master Data Management (MDM) solutions. The contribution provided by this paper consists in the analysis of the IT infrastructure in large, multi-site enterprises, which enabled the identification of problems and challenges related to advanced data analysis in this type of companies.","PeriodicalId":256649,"journal":{"name":"Vietnam. J. Comput. Sci.","volume":"104 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Problems and Challenges Related to Advanced Data Analysis in Multi-Site Enterprises\",\"authors\":\"Helena Dudycz, P. Stefaniak, Pawel Pyda\",\"doi\":\"10.1142/S2196888822500063\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The new generation of industry, i.e. Industry 4.0, pertains to the processing of immense amounts of data, resulting, among other things, from the large-scale use of microcontrollers to control machines, an increase in the scale of automation, the use of the Internet of Things technology — e.g. in sensors installed at different stages of the production process, the implementation of the digital twin concept, and many other technologies designed to collect data (e.g. GPS or RFID). These data are collected in the enterprise’s variety of resources and databases. These data can be a valuable source of information and knowledge if the right approach to advanced data analysis is adopted, which depends, among other things, on the enterprise’s existing IT infrastructure. This paper sets out to present conclusions formulated on the basis of research consisting in the analysis of multinational manufacturing companies’ existing IT infrastructures. Three basic model solutions of IT architecture occurring in multi-site enterprises were identified, which made it possible to identify the main problems stemming from the IT architecture in place and concerning the analysis of data for the needs of company management. Additionally, this paper discusses the challenges faced by multi-site manufacturing companies. One such activity is the modification and expansion of the company’s IT infrastructure, including the implementation of Big Data and Master Data Management (MDM) solutions. The contribution provided by this paper consists in the analysis of the IT infrastructure in large, multi-site enterprises, which enabled the identification of problems and challenges related to advanced data analysis in this type of companies.\",\"PeriodicalId\":256649,\"journal\":{\"name\":\"Vietnam. J. Comput. Sci.\",\"volume\":\"104 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-06-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Vietnam. J. Comput. Sci.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1142/S2196888822500063\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Vietnam. J. Comput. Sci.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1142/S2196888822500063","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

摘要

新一代工业,即工业4.0,涉及大量数据的处理,其中包括大规模使用微控制器来控制机器,自动化规模的增加,物联网技术的使用-例如安装在生产过程不同阶段的传感器,数字孪生概念的实施,以及许多其他旨在收集数据的技术(例如GPS或RFID)。这些数据收集在企业的各种资源和数据库中。如果采用正确的高级数据分析方法,这些数据可以成为有价值的信息和知识来源,这种方法依赖于企业现有的IT基础设施。本文在对跨国制造公司现有IT基础设施进行分析的研究基础上提出了结论。确定了发生在多站点企业中的IT体系结构的三种基本模型解决方案,从而可以确定源于现有IT体系结构的主要问题,以及与公司管理需要的数据分析有关的问题。此外,本文还讨论了多基地制造企业所面临的挑战。其中一项活动是修改和扩展公司的IT基础设施,包括实施大数据和主数据管理(MDM)解决方案。本文的贡献在于对大型多站点企业的IT基础设施进行分析,从而能够识别此类公司中与高级数据分析相关的问题和挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
Problems and Challenges Related to Advanced Data Analysis in Multi-Site Enterprises
The new generation of industry, i.e. Industry 4.0, pertains to the processing of immense amounts of data, resulting, among other things, from the large-scale use of microcontrollers to control machines, an increase in the scale of automation, the use of the Internet of Things technology — e.g. in sensors installed at different stages of the production process, the implementation of the digital twin concept, and many other technologies designed to collect data (e.g. GPS or RFID). These data are collected in the enterprise’s variety of resources and databases. These data can be a valuable source of information and knowledge if the right approach to advanced data analysis is adopted, which depends, among other things, on the enterprise’s existing IT infrastructure. This paper sets out to present conclusions formulated on the basis of research consisting in the analysis of multinational manufacturing companies’ existing IT infrastructures. Three basic model solutions of IT architecture occurring in multi-site enterprises were identified, which made it possible to identify the main problems stemming from the IT architecture in place and concerning the analysis of data for the needs of company management. Additionally, this paper discusses the challenges faced by multi-site manufacturing companies. One such activity is the modification and expansion of the company’s IT infrastructure, including the implementation of Big Data and Master Data Management (MDM) solutions. The contribution provided by this paper consists in the analysis of the IT infrastructure in large, multi-site enterprises, which enabled the identification of problems and challenges related to advanced data analysis in this type of companies.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Improving Arabic Sentiment Analysis Using LSTM Based on Word Embedding Models Synthetic Data Generation for Morphological Analyses of Histopathology Images with Deep Learning Models Generating Popularity-Aware Reciprocal Recommendations Using Siamese Bi-Directional Gated Recurrent Units Network Hyperparameter Optimization of a Parallelized LSTM for Time Series Prediction Natural Language Processing and Sentiment Analysis on Bangla Social Media Comments on Russia-Ukraine War Using Transformers
×
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