Embedding AI and Crowdsourcing in the Big Data Lake

被引：60
|
作者：
O'Leary, Daniel E. [1 ,2 ]
机构：
[1] Univ So Calif, Marshall Sch Business, Los Angeles, CA 90089 USA
[2] Univ So Calif, Leventhal Sch Accounting, Los Angeles, CA 90089 USA
来源：
IEEE INTELLIGENT SYSTEMS | 2014年 / 29卷 / 05期
关键词：
artificial intelligence; Big Data Lake; crowdsourcing; data governance; data warehouses; intelligent systems; master data management;
D O I：
10.1109/MIS.2014.82
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Daniel E. O'Leary examines the notion of the Big Data Lake and contrasts it with decision support-based data warehouses. In addition, some of the risks of the emerging Lake concept that ultimately require data governance are analyzed. O'Leary investigates using different AI and crowdsourcing (human intelligence) applications in that lake in order to integrate disparate data sources, facilitate master data management and analyze data quality. Although data governance often is not seen as a technology issue, it is seen as a critical component of making the Big Data Lake 'work.' © 2001-2011 IEEE.
引用
收藏
页码：70 / 73
页数：4
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