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Importance of Process Mining for Big Data Requirements Engineering


Affiliations
1 Department of Electrical and Computer Engineering and Computer Science, University of Detroit Mercy, Detroit, MI, 48221, United States
 

Requirements engineering (RE), as a part of the project development life cycle, has increasingly been recognized as the key to ensure on-time, on-budget, and goal-based delivery of software projects. RE of big data projects is even more crucial because of the rapid growth of big data applications over the past few years. Data processing, being a part of big data RE, is an essential job in driving big data RE process successfully. Business can be overwhelmed by data and underwhelmed by the information so, data processing is very critical in big data projects. Employing traditional data processing techniques lacks the invention of useful information because of the main characteristics of big data, including high volume, velocity, and variety. Data processing can be benefited by process mining, and in turn, helps to increase the productivity of the big data projects. In this paper, the capability of process mining in big data RE to discover valuable insights and business values from event logs and processes of the systems has been highlighted. Also, the proposed big data requirements engineering framework, named REBD, helps software requirements engineers to eradicate many challenges of big data RE.

Keywords

Big Data, Requirements Engineering, Requirements Elicitation, Data Processing, Knowledge Discovery, Process Mining.
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  • Importance of Process Mining for Big Data Requirements Engineering

Abstract Views: 341  |  PDF Views: 149

Authors

Sandhya Rani Kourla
Department of Electrical and Computer Engineering and Computer Science, University of Detroit Mercy, Detroit, MI, 48221, United States
Eesha Putti
Department of Electrical and Computer Engineering and Computer Science, University of Detroit Mercy, Detroit, MI, 48221, United States
Mina Maleki
Department of Electrical and Computer Engineering and Computer Science, University of Detroit Mercy, Detroit, MI, 48221, United States

Abstract


Requirements engineering (RE), as a part of the project development life cycle, has increasingly been recognized as the key to ensure on-time, on-budget, and goal-based delivery of software projects. RE of big data projects is even more crucial because of the rapid growth of big data applications over the past few years. Data processing, being a part of big data RE, is an essential job in driving big data RE process successfully. Business can be overwhelmed by data and underwhelmed by the information so, data processing is very critical in big data projects. Employing traditional data processing techniques lacks the invention of useful information because of the main characteristics of big data, including high volume, velocity, and variety. Data processing can be benefited by process mining, and in turn, helps to increase the productivity of the big data projects. In this paper, the capability of process mining in big data RE to discover valuable insights and business values from event logs and processes of the systems has been highlighted. Also, the proposed big data requirements engineering framework, named REBD, helps software requirements engineers to eradicate many challenges of big data RE.

Keywords


Big Data, Requirements Engineering, Requirements Elicitation, Data Processing, Knowledge Discovery, Process Mining.

References