FAMDM: An Approach to Handle Semantic Master Data Using Fog-based Architecture

Abstract

AbstractIn digital era, an exponential growth of online transactions leads to a growing need for efficient data storage and management mechanisms. Distributed access to data from different sources generates data quality issues for an organization’s data. Master data management (MDM) has been used to provide a single copy of reference data to avoid data redundancy and quality issues. Master data of an enterprise is organizational data that need less frequent changes, and MDM techniques are used to manage master data, which are a critical component of any organization. Large organizations use standard MDM solutions but due to cost constrains, many small and medium size Enterprises (SMEs) are unable to adopt the MDM solutions. MDM solutions used by SMEs are either based on stand-alone or cloud-based approaches. These opted solutions faced poor response time and distributed access issues, to handle these issues, this paper provides an approach to handle semi-structured master data using semantic techniques. The proposed approach uses fog-based architecture to improve the response time. The proposed approach was validated using Web server-based simulation environment, and comparative analysis of the proposed approach with standard cloud-based approach was provided in this paper.KeywordsData accessMeta dataData processingData sharingOntologies