{"title":"Big Data Based Archiving Management System","authors":"Aysegül Senol Çalim, Cüneyt Kaya, Hakan Yüksel","doi":"10.1109/UBMK52708.2021.9558902","DOIUrl":null,"url":null,"abstract":"The size of data in institutions such as banks is increasing rapidly due to the fact that the number of new products is put into service, the number of customers is increasing rapidly, the number of new applications is put into use due to regulations, and the data that must be kept compulsory such as audit trail records are excessive. When these data remain in existing systems for years, systems and applications become heavy, and the costs of operational processes such as backup and system maintenance increase. For all these problems, the data should be classified and categorized according to the frequency of access, those that do not need instant access to the categorized data should be archived by moving them to secondary and less costly systems and deleted from the source system. The large data-based archiving management system will be developed as a software product, providing more effective access to structural or unstructured data to be archived in the Hadoop ecosystem and bringing cheaper storage costs.","PeriodicalId":106516,"journal":{"name":"2021 6th International Conference on Computer Science and Engineering (UBMK)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 6th International Conference on Computer Science and Engineering (UBMK)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/UBMK52708.2021.9558902","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
The size of data in institutions such as banks is increasing rapidly due to the fact that the number of new products is put into service, the number of customers is increasing rapidly, the number of new applications is put into use due to regulations, and the data that must be kept compulsory such as audit trail records are excessive. When these data remain in existing systems for years, systems and applications become heavy, and the costs of operational processes such as backup and system maintenance increase. For all these problems, the data should be classified and categorized according to the frequency of access, those that do not need instant access to the categorized data should be archived by moving them to secondary and less costly systems and deleted from the source system. The large data-based archiving management system will be developed as a software product, providing more effective access to structural or unstructured data to be archived in the Hadoop ecosystem and bringing cheaper storage costs.