摘要
本论文主要探讨了大数据在电子商务决策支持系统中的应用及其相关策略。首先,论文阐述了大数据的定义、特点与价值,以及电子商务决策支持系统的构成与功能,为后续研究提供了理论基础。论文详细分析了大数据在电子商务决策支持系统中的应用策略,包括数据收集与整合、数据分析与挖掘等方面。大数据在电子商务决策支持系统中的应用也面临着诸多挑战,如数据质量问题、数据处理和分析能力的不足、隐私与安全问题以及法规与政策限制等。针对这些挑战,论文提出了相应的对策,包括提升数据质量、加强数据处理和分析能力、强化隐私与安全保障以及关注法规与政策变化等。本论文的研究不仅有助于深化对大数据在电子商务决策支持系统中应用的认识,也为企业在实际应用中提供了有益的参考和借鉴。通过有效地利用大数据技术和工具,企业可以更好地把握市场机遇,提高决策水平,实现持续发展。
关键词:大数据;电子商务决策支持系统;数据收集与整合
Abstract
This paper mainly discusses the application of big data in e-commerce decision support system and its related strategies. First of all, the paper expounds the definition, characteristics and value of big data, as well as the composition and function of e-commerce decision support system, which provides a theoretical basis for subsequent research. This paper analyzes the application strategy of big data in e-commerce decision support system in detail, including data collection and integration, data analysis and mining. The application of big data in e-commerce decision support systems also faces many challenges, such as data quality issues, insufficient data processing and analysis capabilities, privacy and security issues, and regulatory and policy restrictions. In response to these challenges, the paper proposes corresponding countermeasures, including improving data quality, strengthening data processing and analysis capabilities, strengthening privacy and security guarantees, and paying attention to regulatory and policy changes. The research of this paper not only helps to deepen the understanding of the application of big data in e-commerce decision support system, but also provides useful reference and reference for enterprises in practical application. By effectively utilizing big data technologies and tools, companies can better grasp market opportunities, improve decision-making, and achieve sustainable development.
Keywords: Big data; Electronic commerce decision support system; Data collection and integration
目 录
摘要 I
Abstract II
一、绪论 1
(一)研究背景及意义 1
(二)国内外研究现状 1
二、理论基础 2
(一)大数据的定义、特点与价值 2
(二)电子商务决策支持系统的构成与功能 2
三、大数据在电子商务决策支持系统中的应用策略 4
(一)数据收集与整合策略 4
(二)数据分析与挖掘策略 4
(三)决策支持与优化策略 5
四、大数据在电子商务决策支持系统中应用的挑战 6
(一)数据质量问题 6
(二)数据处理和分析能力 6
(三)隐私与安全问题 6
(四)法规与政策限制 7
五、大数据在电子商务决策支持系统中应用的对策 8
(一)提升数据质量 8
(二)加强数据处理和分析能力 8
(三)强化隐私与安全保障 9
(四)关注法规与政策变化 9
结 论 10
参考文献 11