Purpose The purpose of this paper is to explore various limitations of conventional mining systems in extracting useful buying patterns from retail transactional databases flooded with Big Data. The key objective is to assist retail business owners to better understand the purchase needs of their customers and hence to attract customers to physical retail stores away from competitor e-commerce websites. Design/methodology/approach This paper employs a systematic and category-based review of relevant literature to explore the challenges possessed by Big Data for retail industry followed by discussion and implementation of association between MapReduce based Apriori association mining and Hadoop-based intelligent cloud architecture. Findings The findings reveal that conventional mining algorithms have not evolved to support Big Data analysis as required by modern retail businesses. They require a lot of resources such as memory and computational engines. This study aims to develop MR-Apriori algorithm in the form of IRM tool to address all these issues in an efficient manner. Research limitations/implications The paper suggests that a lot of research is yet to be done in market basket analysis, if full potential of cloud-based Big Data framework is required to be utilized. Originality/value This research arms the retail business owners with innovative IRM tool to easily extract comprehensive knowledge of useful buying patterns of customers to increase profits. This study experimentally verifies the effectiveness of proposed algorithm.

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This research service provides an original perspective on how artificial intelligence (AI) is making its way into the retail sector. Retail has entered a new era where ECommerce and technology bellwethers like Alibaba, Amazon, Apple, Baidu, Facebook, Google, Microsoft, and Tencent have raised consumers' expectations. AI is enabling automated decision-making with accuracy and speed, based on data analytics, coupled with self- learning abilities. The retail sector has witnessed the dramatic evolution with the rapid digitalization of communication (i.e. Internet) and; smart phones and devices. Customer is no longer the same as they became more empowered by smart devices which has entirely prevailed their expectation, habits, style of shopping and investigating the shops. This article outlines the Significant innovation done in retails which helped them to evolve such as Artificial Intelligence (AI), Big data and Internet of Things (IoT), Chatbots, Robots. This article further also discusses the ideology of various author on how AI become more profitable and a close asset to customers and retailers.

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