A. Massaro, Valeria Vitti, Palo Lisco, A. Galiano, Nicola Savino
{"title":"A Business Intelligence Platform Implemented in a Big Data System Embedding Data Mining: A Case of Study","authors":"A. Massaro, Valeria Vitti, Palo Lisco, A. Galiano, Nicola Savino","doi":"10.5121/IJDKP.2019.9101","DOIUrl":null,"url":null,"abstract":"In this work is discussed a case study of a business intelligence –BI- platform developed within the framework of an industry project by following research and development –R&D- guidelines of ‘Frascati’. The proposed results are a part of the output of different jointed projects enabling the BI of the industry ACI Global working mainly in roadside assistance services. The main project goal is to upgrade the information system, the knowledge base –KB- and industry processes activating data mining algorithms and big data systems able to provide gain of knowledge. The proposed work concerns the development of the highly performing Cassandra big data system collecting data of two industry location. Data are processed by data mining algorithms in order to formulate a decision making system oriented on call center human resources optimization and on customer service improvement. Correlation Matrix, Decision Tree and Random Forest Decision Tree algorithms have been applied for the testing of the prototype system by finding a good accuracy of the output solutions. The Rapid Miner tool has been adopted for the data processing. The work describes all the system architectures adopted for the design and for the testing phases, providing information about Cassandra performance and showing some results of data mining processes matching with industry BI strategies.","PeriodicalId":131153,"journal":{"name":"International Journal of Data Mining & Knowledge Management Process","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"17","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Data Mining & Knowledge Management Process","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5121/IJDKP.2019.9101","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 17
Abstract
In this work is discussed a case study of a business intelligence –BI- platform developed within the framework of an industry project by following research and development –R&D- guidelines of ‘Frascati’. The proposed results are a part of the output of different jointed projects enabling the BI of the industry ACI Global working mainly in roadside assistance services. The main project goal is to upgrade the information system, the knowledge base –KB- and industry processes activating data mining algorithms and big data systems able to provide gain of knowledge. The proposed work concerns the development of the highly performing Cassandra big data system collecting data of two industry location. Data are processed by data mining algorithms in order to formulate a decision making system oriented on call center human resources optimization and on customer service improvement. Correlation Matrix, Decision Tree and Random Forest Decision Tree algorithms have been applied for the testing of the prototype system by finding a good accuracy of the output solutions. The Rapid Miner tool has been adopted for the data processing. The work describes all the system architectures adopted for the design and for the testing phases, providing information about Cassandra performance and showing some results of data mining processes matching with industry BI strategies.
在这项工作中,讨论了一个商业智能- bi -平台的案例研究,该平台是在一个行业项目的框架内按照“Frascati”的研发指导方针开发的。建议的结果是不同联合项目的一部分,使ACI Global的BI主要从事道路援助服务。该项目的主要目标是升级信息系统、知识库(kb)以及激活数据挖掘算法和能够提供知识增益的大数据系统的行业流程。提出的工作涉及高性能Cassandra大数据系统的开发,该系统可以收集两个行业位置的数据。通过数据挖掘算法对数据进行处理,形成了一个面向呼叫中心人力资源优化和客户服务改进的决策系统。应用相关矩阵、决策树和随机森林决策树算法对原型系统进行测试,获得了较好的输出解精度。数据处理采用了Rapid Miner工具。该工作描述了设计和测试阶段采用的所有系统架构,提供了有关Cassandra性能的信息,并显示了与行业BI策略匹配的数据挖掘过程的一些结果。