DIRTY DATA CLEANING FOR THE BETTERMENT OF ONLINE BUSINESSES

Abstract

F-commerce a very new and popular addition of F-commerce that became popular among young entrepreneurs and young generation. F-commerce emerging getting as one of the way of unemployment solution specially during the pandemic situation. The success, competence, reliability and sustainability of f-commerce relies on the quality of its relevant data. However, it is very challenging to maintain the quality of data generated from the F-commerce platform which are produced from numerous sources. In F-commerce Generally, data comes from various sources and communication channels hence it is troublesome to integrate and manage data compare to conventional business data. There are several methods, tools and exists that is being used for cleaning dirty data. This research highlights the current literature reviews of dirty data, discusses existing tools and techniques. The review finds out a finding that even though several works exist those works have some constraints and none of the existing works addressing the specific problem in the context of an F-commerce platform. Based on the finding it provides a recommendation for future research direction to encounter the problem of cleaning dirty data in the F-commerce platform.