Vahid Khiabani, Middle Tennessee State University, USA

MapReduce is a powerful programming model that leverages distributed systems to handle and process large-scale datasets efficiently. It has found extensive application not only in academic research but also in diverse industrial sectors, where data analysis plays a crucial role in decision-making and operational efficiency. Despite its advantages, there remains a significant gap between the capabilities of developers who implement MapReduce and the requirements of data analysts who wish to use it for in-depth data exploration and analysis. Developers of MapReduce frameworks often lack a comprehensive understanding of the nuances of data analysis, which can lead to challenges in producing the specific analytical outputs that stakeholders require. On the other hand, data analysts typically possess the domain knowledge needed for insightful data interpretation but often struggle with the technical complexities of programming in MapReduce. This gap results in communication barriers and hampers the potential for effective collaboration, ultimately making it difficult for developers to meet the analytical needs of their users. To bridge this divide, this study proposes the development of a novel MapReduce analysis process management system grounded in Business Process Management (BPM) principles. The proposed system aims to serve as an intermediary tool that enhances communication and collaboration between MapReduce developers and data analysts. By providing structured processes and workflows, this system will facilitate the sharing of knowledge and requirements between the two groups. Moreover, the system is designed to be adaptable, allowing for quick and flexible responses to modifications in analysis procedures. This adaptability is essential in today’s fast-paced data environment, where analytical demands can change rapidly. By implementing this management system, organizations can ensure that developers and analysts work together more effectively, leading to improved analysis outcomes and greater satisfaction for all stakeholders involved.

APA:
Khiabani, V. (2023). A Study on Managing the Data Analysis Process in MapReduce Using Business Process Management (BPM). Journal of Science and Engineering Management, 3(1), 1-12. https://doi.org/10.33832/jsem.2022.3.1.01