Approaches for value extraction on big data

Xiaoyong DU; Yueguo CHEN

doi:10.11959/j.issn.2096-0271.2017015

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Approaches for value extraction on big data

TOPIC:BIG DATA MANAGEMENT AND ANALYTICS | 更新时间：2024-06-03

- Approaches for value extraction on big data
- Big data research Vol. 3, Issue 2, Pages: 2017015(2017)
- 作者机构：
  
  1. 数据工程与知识工程教育部重点实验室（中国人民大学），北京 100872
  2. 中国人民大学信息学院，北京 100872
- 作者简介：
- 基金信息：
- DOI：10.11959/j.issn.2096-0271.2017015
  CLC： TP391.1
- Online First：2017-03，
  
  Published：20 March 2017
- 稿件说明：
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Xiaoyong DU, Yueguo CHEN. Approaches for value extraction on big data[J]. Big data research, 2017, 3(2): 2017015.
DOI：

Xiaoyong DU, Yueguo CHEN. Approaches for value extraction on big data[J]. Big data research, 2017, 3(2): 2017015. DOI： 10.11959/j.issn.2096-0271.2017015.

摘要

大数据的价值有不同的体现形式和发现价值的途径。总结了从大数据中发现价值的3种基本途径：数据服务、数据分析与数据探索，并对它们的特点进行了分析和对比。数据服务通过提供高性能和高并发的数据访问从微观层面体现数据价值；数据分析侧重利用统计模型的方法在宏观层面上对大数据进行处理，通过产生数据洞察的形式体现数据价值；数据探索侧重通过交互模型在微观和宏观的不断变换，引导用户浏览和发现数据的价值。

Abstract

The value of big data can be presented in different means，and therefore it has different ways to extract the value out of big data.Three approaches of value extraction on big data:data service，data analytics，and data exploration were summarized.The characteristics of these approaches were analyzed and compared.In summary，data service reflects the value of data from the micro-level by supporting high-performance and high-throughput read and write operations.Data analysis focuses on the usage of statistical models to generalize data distribution at macro-level，and it extracts values by generating insights from data.Data exploration focuses on interactive models in the constant interchange of micro-level and macrolevel to guide the users browse and discover values out of the data.

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references

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