International Journal of Computer
Trends and Technology

Research Article | Open Access | Download PDF

Volume 58 | Number 1 | Year 2018 | Article Id. IJCTT-V58P102 | DOI : https://doi.org/10.14445/22312803/IJCTT-V58P102

Simple analytics in Retail Sales Data using Hadoop

R.R. Karthikeyan , Dr. B Raghu

Citation :

R.R. Karthikeyan , Dr. B Raghu, "Simple analytics in Retail Sales Data using Hadoop," International Journal of Computer Trends and Technology (IJCTT), vol. 58, no. 1, pp. 14-19, 2018. Crossref, https://doi.org/10.14445/22312803/IJCTT-V58P102

Abstract

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. In-store 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 in-demand products, helping to optimize the supply chain.

Keywords

Big Data Analytics, Hadoop,Retail analytics.

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