Software Engineering for Big Data Application Development: Systematic Literature Survey Using Snowballing
Prateek Juneja, Preeti Kaur · 2019 International Conference on Computing, Power and Communication Technologies (GUCON) · 2019
The Big Data Analytics is revolutionizing the Information and Technology sector. Researchers and corporate giants are investing their resources into developing big data application softwares that can provide them useful insight about collected data efficiently and help them to make strategic decisions. But failure rates for big data applications is rather high than anticipated. Hence there is a need to revisit software engineering methodologies and software processes and make them more adaptable for Big Data Applications. Objective: In this paper we are doing systematic literature review of research papers that focuses on software engineering methodologies and software processes for big data applications. Method: Total of 695 papers were reviewed and 22 papers were found relevant according to research question/s using snowballing method. Result: The research papers helped in finding the methodologies and requirements for developing big data applications.