{"title":"基于OLAP的多维数据分布监控","authors":"Yifan Mao, Shasha Huang, Shuo Cui, Haifeng Wang, Junyan Zhang, Wenhao Ding","doi":"10.1109/ITCA52113.2020.00070","DOIUrl":null,"url":null,"abstract":"With the rapid development of the Internet, society is gradually entering the information age, and various data in enterprises have become the most important strategic core resources of all enterprises. The operation and decision-making of enterprises all require a large amount of data analysis. Nowadays, many companies do not pay enough attention to the monitoring of data asset distribution. In addition, various internal systems such as financial management and ERP systems are relatively independent. Each system has its own data organization standard, which makes it difficult to conduct a unified management of data. This also directly leads to the one-sided and subjective problem of enterprise managers' distribution of data assets. With the construction of the data center of each enterprise, the data of each system is aggregated to the center through data integration technology. Therefore, all enterprises need to build a multi-dimensional data distribution monitoring model around data links to comprehensively monitor the status of various data distributions across the company's entire network, and improve data service capabilities and sharing capabilities as well as the company's operational capabilities. This article uses OLAP technology to construct a multi-dimensional data distribution monitoring model for the data link in the process of power enterprise data integration. This article first selects the dimensions and metrics that need to be monitored in the multidimensional data, and then constructs the conceptual model, logical model and physical model of the multidimensional data using on line analytical processing technology. Finally, an example analysis of OLAP system architecture based on B/S structure is realized. The overall data distribution of the enterprise can be grasped by analyzing the various dimensions of the data link, such as System type, location distribution, and time.","PeriodicalId":103309,"journal":{"name":"2020 2nd International Conference on Information Technology and Computer Application (ITCA)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Multi dimensional data distribution monitoring based on OLAP\",\"authors\":\"Yifan Mao, Shasha Huang, Shuo Cui, Haifeng Wang, Junyan Zhang, Wenhao Ding\",\"doi\":\"10.1109/ITCA52113.2020.00070\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With the rapid development of the Internet, society is gradually entering the information age, and various data in enterprises have become the most important strategic core resources of all enterprises. The operation and decision-making of enterprises all require a large amount of data analysis. Nowadays, many companies do not pay enough attention to the monitoring of data asset distribution. In addition, various internal systems such as financial management and ERP systems are relatively independent. Each system has its own data organization standard, which makes it difficult to conduct a unified management of data. This also directly leads to the one-sided and subjective problem of enterprise managers' distribution of data assets. With the construction of the data center of each enterprise, the data of each system is aggregated to the center through data integration technology. Therefore, all enterprises need to build a multi-dimensional data distribution monitoring model around data links to comprehensively monitor the status of various data distributions across the company's entire network, and improve data service capabilities and sharing capabilities as well as the company's operational capabilities. This article uses OLAP technology to construct a multi-dimensional data distribution monitoring model for the data link in the process of power enterprise data integration. This article first selects the dimensions and metrics that need to be monitored in the multidimensional data, and then constructs the conceptual model, logical model and physical model of the multidimensional data using on line analytical processing technology. Finally, an example analysis of OLAP system architecture based on B/S structure is realized. The overall data distribution of the enterprise can be grasped by analyzing the various dimensions of the data link, such as System type, location distribution, and time.\",\"PeriodicalId\":103309,\"journal\":{\"name\":\"2020 2nd International Conference on Information Technology and Computer Application (ITCA)\",\"volume\":\"51 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 2nd International Conference on Information Technology and Computer Application (ITCA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ITCA52113.2020.00070\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 2nd International Conference on Information Technology and Computer Application (ITCA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITCA52113.2020.00070","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Multi dimensional data distribution monitoring based on OLAP
With the rapid development of the Internet, society is gradually entering the information age, and various data in enterprises have become the most important strategic core resources of all enterprises. The operation and decision-making of enterprises all require a large amount of data analysis. Nowadays, many companies do not pay enough attention to the monitoring of data asset distribution. In addition, various internal systems such as financial management and ERP systems are relatively independent. Each system has its own data organization standard, which makes it difficult to conduct a unified management of data. This also directly leads to the one-sided and subjective problem of enterprise managers' distribution of data assets. With the construction of the data center of each enterprise, the data of each system is aggregated to the center through data integration technology. Therefore, all enterprises need to build a multi-dimensional data distribution monitoring model around data links to comprehensively monitor the status of various data distributions across the company's entire network, and improve data service capabilities and sharing capabilities as well as the company's operational capabilities. This article uses OLAP technology to construct a multi-dimensional data distribution monitoring model for the data link in the process of power enterprise data integration. This article first selects the dimensions and metrics that need to be monitored in the multidimensional data, and then constructs the conceptual model, logical model and physical model of the multidimensional data using on line analytical processing technology. Finally, an example analysis of OLAP system architecture based on B/S structure is realized. The overall data distribution of the enterprise can be grasped by analyzing the various dimensions of the data link, such as System type, location distribution, and time.