统计研究

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大数据与数据工程学

李腊生等   

  • 出版日期:2015-09-15 发布日期:2015-09-17

Big Data and Data Engineering

Li Lasheng etal   

  • Online:2015-09-15 Published:2015-09-17

摘要: 大数据的冲击并非是对以样本数据为对象的统计学的颠覆,而是对现代统计学的扩展。本文结合大数据的相关特征,以数据经济价值的扩展为切入点,从数据价值挖掘的角度论证了数据挖掘与大数据分析的关系,探讨了大数据背景下数据衍生品的创造与数据工程学创建的必要性。在此基础上,参照“金融工程学”的概念及学科体系,对“数据工程学”的概念进行了界定,并对数据工程学学科体系构建的相关理论基础、主要研究内容与分析技术进行了归纳与说明。

关键词: 大数据, 数据衍生品, 数据工程, 数据价值有效

Abstract: Big data is the extension but not the overturn to the modern statistics. According to the relevant characteristics of the big data and the expansion of the data’s economic value, it demonstrates the relationship between the data mining and big data analysis from the perspective of data value mining, and discusses the necessity of the data derivatives and the data engineering. It defines the concept of “data engineering” by the idea of “financial engineering” and its conceptual framework. It also generalizes and states the theoretical basis of the data engineering, the main research contents and technologies.

Key words: Big Data, Data derivatives, Data Engineering, Valid Data Value