An Empirical Research on Service-Oriented Architecture (SOA) for Data Exchange in BIGDATA Systems

Abstract

Service-Oriented Architecture is a method for scheming dealing and organizing systems that represent ecofriendly business functionality. The objective of this study is to find out the critical success factors that need to implement SOA in BIG DATA systems. Our study aimed at classifying these erroneous performs in execution of SOA. The acceptance of SOA has interested creators to text its requests and applications. The analysed results would be very useful for researchers who would like to implement SOA with BIG DATA systems. SOA lead numerous advantages such as value-added flexibility and appropriate alignment among processes as well as reduced cost of integration and maintenance. Generally, BIG DATA anxieties large-volume, composite, rising figures groups with numerous, self-directed sources. BIG DATA claims where data gathering has grownup extremely and is elsewhere the aptitude of usually used software utensils to detention, accomplish and development within the rise [1]. The greatest essential task for the BIG DATA applications is to discover the large volumes of data and excerpt valuable material or information for upcoming actions. The main purpose of this study is to identify the important factors that are needed to implement SOA in BIG DATA systems. Zhang and Yang suggests a reengineering approach which will restructure the legacy systems that leads to SOA by considering of an organization. This paper also express various challenges of SOA and identify the problems that improve SOA based services for data exchange in BIG DATA systems.