{"title":"作为关键业务数据科学学科的部署","authors":"T. Davenport, Katie Malone","doi":"10.1162/99608F92.90814C32","DOIUrl":null,"url":null,"abstract":"Column Editors’ Note: In this article, we focus on a key problem in industry: getting data science models deployed into production within organizations. The tasks and skills involved in deployment are often not considered as a key component of data science initiatives, but they are critical to data science success. We describe evidence of the deployment problem, the components of deployment, and how some campus-based business analytics degree programs attempt to inculcate deployment skills.","PeriodicalId":194618,"journal":{"name":"Issue 3.1, Winter 2021","volume":"753 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"Deployment as a Critical Business Data Science Discipline\",\"authors\":\"T. Davenport, Katie Malone\",\"doi\":\"10.1162/99608F92.90814C32\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Column Editors’ Note: In this article, we focus on a key problem in industry: getting data science models deployed into production within organizations. The tasks and skills involved in deployment are often not considered as a key component of data science initiatives, but they are critical to data science success. We describe evidence of the deployment problem, the components of deployment, and how some campus-based business analytics degree programs attempt to inculcate deployment skills.\",\"PeriodicalId\":194618,\"journal\":{\"name\":\"Issue 3.1, Winter 2021\",\"volume\":\"753 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-02-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Issue 3.1, Winter 2021\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1162/99608F92.90814C32\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Issue 3.1, Winter 2021","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1162/99608F92.90814C32","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Deployment as a Critical Business Data Science Discipline
Column Editors’ Note: In this article, we focus on a key problem in industry: getting data science models deployed into production within organizations. The tasks and skills involved in deployment are often not considered as a key component of data science initiatives, but they are critical to data science success. We describe evidence of the deployment problem, the components of deployment, and how some campus-based business analytics degree programs attempt to inculcate deployment skills.