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如今大数据的商业应用主要集中在行为标签、智能推荐、管理系统、数据整理与展示以及广告检测智能系统等,国内外大量企业都已经开始或准备开始利用大数据创造新的利润增长点。虽然大数据在商业应用中拥有巨大潜力,但是其在应用中也存在一些需要思考的问题,包括计算速度制约全数据计算、海量数据的假规律风险、断裂数据和封闭数据以及缺失数据。在肯定大数据应用的进步和成果的同时,只有思辨地看到大数据应用过程中还存在的误区,正视当下需要思考和解决的问题,才能更清晰地理解大数据应用的商业逻辑以及局限。
Nowadays, the commercial applications of big data mainly focus on behavioral labeling, intelligent recommendation, management system, data collation and display, and advertisement detection intelligent system. Many domestic and foreign enterprises have started or are ready to start using big data to create new profit growth points. Although big data has great potential in commercial applications, there are some problems that need to be considered in the application. For example, computing speed constrains full data calculation, fake regular risk of mass data, fracture data and closed data, and missing data. While affirming the progress and achievements in the application of big data, it is only by judiciously seeing the misunderstandings in the application of big data and facing the current problems that need to be considered and solved in order to understand the business logic and limitations of big data applications more clearly.