{"title":"用于劳动力管理决策的轨迹数据仓库解决方案","authors":"Georgia Garani, Dimitrios Tolis, Ilias K. Savvas","doi":"10.1016/j.dsm.2023.03.002","DOIUrl":null,"url":null,"abstract":"<div><p>In modern workforce management, the demand for new ways to maximize worker satisfaction, productivity, and security levels is endless. Workforce movement data such as those source data from an access control system can support this ongoing process with subsequent analysis. In this study, a solution to attaining this goal is proposed, based on the design and implementation of a data mart as part of a dimensional trajectory data warehouse (TDW) that acts as a repository for the management of movement data. A novel methodological approach is proposed for modeling multiple spatial and temporal dimensions in a logical model. The case study presented in this paper for modeling and analyzing workforce movement data is to support human resource management decision-making and the following discussion provides a representative example of the contribution of a TDW in the process of information management and decision support systems. The entire process of exporting, cleaning, consolidating, and transforming data is implemented to achieve an appropriate format for final import. Structured query language (SQL) queries demonstrate the convenience of dimensional design for data analysis, and valuable information can be extracted from the movements of employees on company premises to manage the workforce efficiently and effectively. Visual analytics through data visualization support the analysis and facilitate decision-making and business intelligence.</p></div>","PeriodicalId":100353,"journal":{"name":"Data Science and Management","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A trajectory data warehouse solution for workforce management decision-making\",\"authors\":\"Georgia Garani, Dimitrios Tolis, Ilias K. Savvas\",\"doi\":\"10.1016/j.dsm.2023.03.002\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>In modern workforce management, the demand for new ways to maximize worker satisfaction, productivity, and security levels is endless. Workforce movement data such as those source data from an access control system can support this ongoing process with subsequent analysis. In this study, a solution to attaining this goal is proposed, based on the design and implementation of a data mart as part of a dimensional trajectory data warehouse (TDW) that acts as a repository for the management of movement data. A novel methodological approach is proposed for modeling multiple spatial and temporal dimensions in a logical model. The case study presented in this paper for modeling and analyzing workforce movement data is to support human resource management decision-making and the following discussion provides a representative example of the contribution of a TDW in the process of information management and decision support systems. The entire process of exporting, cleaning, consolidating, and transforming data is implemented to achieve an appropriate format for final import. Structured query language (SQL) queries demonstrate the convenience of dimensional design for data analysis, and valuable information can be extracted from the movements of employees on company premises to manage the workforce efficiently and effectively. Visual analytics through data visualization support the analysis and facilitate decision-making and business intelligence.</p></div>\",\"PeriodicalId\":100353,\"journal\":{\"name\":\"Data Science and Management\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Data Science and Management\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2666764923000103\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Data Science and Management","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2666764923000103","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A trajectory data warehouse solution for workforce management decision-making
In modern workforce management, the demand for new ways to maximize worker satisfaction, productivity, and security levels is endless. Workforce movement data such as those source data from an access control system can support this ongoing process with subsequent analysis. In this study, a solution to attaining this goal is proposed, based on the design and implementation of a data mart as part of a dimensional trajectory data warehouse (TDW) that acts as a repository for the management of movement data. A novel methodological approach is proposed for modeling multiple spatial and temporal dimensions in a logical model. The case study presented in this paper for modeling and analyzing workforce movement data is to support human resource management decision-making and the following discussion provides a representative example of the contribution of a TDW in the process of information management and decision support systems. The entire process of exporting, cleaning, consolidating, and transforming data is implemented to achieve an appropriate format for final import. Structured query language (SQL) queries demonstrate the convenience of dimensional design for data analysis, and valuable information can be extracted from the movements of employees on company premises to manage the workforce efficiently and effectively. Visual analytics through data visualization support the analysis and facilitate decision-making and business intelligence.