Retailing Analysis Using Hadoop and Apache Hive.

Convenience is an important factor for people in daily activities particularly for users who consume goods and services and also for retailers who provide such services. The retail industry took infant steps in the early 20th century across most of Europe and America. However, there was a considerable surge in the rise of supermarkets and hypermarkets in 2nd half of the century as they provided a convenient all-in-one-stop experience for customers. This subsequently created a huge growth of data in retail stores which presented a challenge for store owners to interpret with traditional business intelligence tools. Therefore, there was a need for real-time analytic tools to handle large datasets in sizes of up to Terabyte magnitudes. Query languages such as Hive and Pig became prominent in the analysis of customer data to ensure continued convenient experience for customers and quality provision of services for retailers. In this paper we analyze the underlying factors that have made Hive to be effective for the retail industry. [ABSTRACT FROM AUTHOR]