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Using global research infrastructure with big (commercial) data: Modelling consumer behaviour in China

机译:将全球研究基础设施与大(商业)数据结合使用:对中国消费者行为进行建模

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The advent of globally distributed computing services and network access allows ‘big data’ on consumption to be used to model, explain and predict consumer behavior at resolutions that range from individual cities to whole countries. Given access to suitable infrastructure, the most significant challenge is to create conditions under which ‘Data Scientists’ may access and manipulate the required data whilst observing individual, national, and commercial constraints set by the type and location of the data. This paper draws on the experience of building the first Global Computing Grid to connect collaborating sites in three continents and describes the architecture of an embedded analytical facility installed within a Chinese commercial organisation that has enabled collaborative analysis of millions of consumer records. We report how this access has provided new insights into consumer behaviour within China ranging from testing strategic models of economic development to exploring ‘digital exclusion’ and the impact of migration on technology adoption.
机译:全球分布的计算服务和网络访问的出现使得消费的“大数据”可以用于建模,解释和预测消费者行为,其分辨率范围从单个城市到整个国家。如果能够使用合适的基础架构,那么最大的挑战就是创造条件,让“数据科学家”可以访问和操纵所需的数据,同时遵守由数据类型和位置设置的个人,国家和商业限制。本文借鉴了建立第一个全球计算网格以连接三大洲的协作站点的经验,并描述了安装在中国商业组织中的嵌入式分析设施的体系结构,该设施已实现了对数百万条消费者记录的协作分析。我们报告了这种访问方式如何提供对中国消费者行为的新见解,从测试经济发展的战略模型到探索“数字排斥”以及迁移对技术采用的影响。

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