商业智能解决方案的数据科学预测分析

P. Wazurkar, R. S. Bhadoria, Dhananjai Bajpai
{"title":"商业智能解决方案的数据科学预测分析","authors":"P. Wazurkar, R. S. Bhadoria, Dhananjai Bajpai","doi":"10.1109/CSNT.2017.8418568","DOIUrl":null,"url":null,"abstract":"In modern era of computing, organizations are focusing on the better utilization of technology and surviving to gear-up with global business demand. Such competition is acting as a driving force for its business to cope-up the data which generated every second of minute. This data needs to figure out and segregated with information which is required for is business growth model. The Predictive Analytics (PA) uses various algorithms to find out different patterns in large data that might suggest the efficient behavior for business solution. This paper provides a conceptual decision making process for data using predictive analysis to maximize the success ratio for handling large dataset. Today, different technologies like cloud computing, SOA, are together transforming information technology but in turn, are imposing new complexities to the data computation. Due to such advances in technologies, and it requires rapid and dynamic data analysis for structured and unstructured data.","PeriodicalId":382417,"journal":{"name":"2017 7th International Conference on Communication Systems and Network Technologies (CSNT)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"33","resultStr":"{\"title\":\"Predictive analytics in data science for business intelligence solutions\",\"authors\":\"P. Wazurkar, R. S. Bhadoria, Dhananjai Bajpai\",\"doi\":\"10.1109/CSNT.2017.8418568\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In modern era of computing, organizations are focusing on the better utilization of technology and surviving to gear-up with global business demand. Such competition is acting as a driving force for its business to cope-up the data which generated every second of minute. This data needs to figure out and segregated with information which is required for is business growth model. The Predictive Analytics (PA) uses various algorithms to find out different patterns in large data that might suggest the efficient behavior for business solution. This paper provides a conceptual decision making process for data using predictive analysis to maximize the success ratio for handling large dataset. Today, different technologies like cloud computing, SOA, are together transforming information technology but in turn, are imposing new complexities to the data computation. Due to such advances in technologies, and it requires rapid and dynamic data analysis for structured and unstructured data.\",\"PeriodicalId\":382417,\"journal\":{\"name\":\"2017 7th International Conference on Communication Systems and Network Technologies (CSNT)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"33\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 7th International Conference on Communication Systems and Network Technologies (CSNT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CSNT.2017.8418568\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 7th International Conference on Communication Systems and Network Technologies (CSNT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CSNT.2017.8418568","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 33

摘要

在现代计算时代,组织正专注于更好地利用技术和生存,以适应全球业务需求。这种竞争正成为其业务应对每分每秒产生的数据的推动力。这些数据需要与业务增长模型所需的信息进行区分和分离。预测分析(PA)使用各种算法在大数据中发现可能建议业务解决方案的有效行为的不同模式。本文提供了一个概念性的数据决策过程,利用预测分析来最大化处理大型数据集的成功率。今天,云计算、SOA等不同的技术共同改变了信息技术,但反过来又给数据计算带来了新的复杂性。由于技术的进步,它需要对结构化和非结构化数据进行快速和动态的数据分析。
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
Predictive analytics in data science for business intelligence solutions
In modern era of computing, organizations are focusing on the better utilization of technology and surviving to gear-up with global business demand. Such competition is acting as a driving force for its business to cope-up the data which generated every second of minute. This data needs to figure out and segregated with information which is required for is business growth model. The Predictive Analytics (PA) uses various algorithms to find out different patterns in large data that might suggest the efficient behavior for business solution. This paper provides a conceptual decision making process for data using predictive analysis to maximize the success ratio for handling large dataset. Today, different technologies like cloud computing, SOA, are together transforming information technology but in turn, are imposing new complexities to the data computation. Due to such advances in technologies, and it requires rapid and dynamic data analysis for structured and unstructured data.
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
Smart input: Provide mouse and keyboard input to a PC from android devices A hybrid approach for human skin detection Correlating multiple events and data in an ethernet network Data visualization through R and Azure for scaling machine training sets Robust machine learning of the complex-valued neurons
×
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