期刊名称：International Journal of Computer Trends and Technology
电子版ISSN：2231-2803
出版年度：2018
卷号：58
期号：1
页码：14-19
DOI：10.14445/22312803/IJCTT-V58P102
出版社：Seventh Sense Research Group
摘要：Data is collected from point of sale transactions, inventory status and pricing, competitive intelligence, social media, weather, and customers (scrubbed of personal identification) and then pulled together on the Hadoop Platform, allowing for a centralized analysis of correlations and patterns that are relevant to improving business. Instore and online purchases, Twitter trends, local sports events, and weather buying patterns are analyzed by big data algorithms to build innovative applications that personalize customer experience while increasing the efficiency of logistics. Point of sale transactions are analyzed to provide product recommendations or discounts, based on which products were bought together or before another product. Predictive analytics is used to know what products sell more on particular days in certain kinds of stores, to reduce overstock and to remain properly stocked on the most indemand products, helping to optimize the supply chain.
关键词：– Big Data Analytics; Hadoop; Retail analytics.
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