{"title":"The Moat Effects of Data Swamps","authors":"B. Beaton","doi":"10.1109/AI4I.2018.8665705","DOIUrl":null,"url":null,"abstract":"This work chronicles a strategy that became popular among early data scientists for explaining undesirable research outcomes and research process slowdowns to both themselves and clients.","PeriodicalId":133657,"journal":{"name":"2018 First International Conference on Artificial Intelligence for Industries (AI4I)","volume":"299 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 First International Conference on Artificial Intelligence for Industries (AI4I)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AI4I.2018.8665705","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This work chronicles a strategy that became popular among early data scientists for explaining undesirable research outcomes and research process slowdowns to both themselves and clients.
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