Abstract
The majority of publications around big data analytics are centred on technical algorithms or systems development. While research has been conducted on the use of big data analytics there is an apparent lack of studies which focus on industry-specific usage in South Africa. The purpose of the study was to assess the usage of big data analytics in the retail industries in South Africa. The benefits of using big data analytics are not specific to a particular industry. Retailers, for example, can use big data analytics to gain new insights about their customers in order to inform decision making around pricing and marketing. The usage of big data analytics was assessed by collecting data from interviews with retailers, big data vendors and professional services. The main finding of the study was that South African retailers are not using big data analytics. Some retailers are, however, using big data analytic platforms to improve the speed of processing large amounts of structured data and to deliver information cost effectively. The findings show that South African retailers find it difficult to identify a use case to justify the investment required for using big data analytics. Key words: Big data, data analytics, retail industry.
Highlights
Big data is often described as a collection of large and complex datasets which are difficult to capture, store, manage and analyse effectively using current database management software and concepts (Fan and Bifet, 2013; Kaisler et al, 2013)
In order to achieve the aim of the research, information was collected by interviewing retailers, big data analytics vendors and professional services
The purpose of this study was to assess the use of big data analytics in the retail industry in South Africa
Summary
Big data is often described as a collection of large and complex datasets which are difficult to capture, store, manage and analyse effectively using current database management software and concepts (Fan and Bifet, 2013; Kaisler et al, 2013). Big data is not a new concept, and companies such as Ebay, LinkedIn, and Facebook have been collecting big data since the mid-2000s (Davenport, 2013). Today a number of companies are collecting and processing large amounts of data on a daily basis. With the overwhelming amount of data being generated at a terabyte and even a petabyte scale, there is a need for big data analytics to obtain insights from big data (Chen et al, 2012; Singh and Singh, 2012).Big data analytics refers to a collection of analytic techniques and technologies which have been designed to analyse big data to inform decision making (Fisher, et al, 2012; Kwon et al, 2014; Russom, 2011).
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