Big data challenges: Prioritizing by decision-making process using Analytic Network Process technique

Abstract

This paper presents an innovative technique to find out the most influential challenge faced by big data. Presently, the key challenges faced by big data are security, privacy, and accuracy. To prioritize the most influential factor among the three, we need to select the suitable factor that accomplishes our objectives within the available resources. In this study, we propose the Analytic Network Process (ANP) technique for evaluating these challenges. The study also appraises the ANP model in comparison with the priorities of all competing challenges inside the big data. The secondary data has been taken for the ANP analysis from numerous scholarly articles focusing on big data. In our analysis, we have proposed a policy assessment of the relation between big data characteristics and the challenges; it further prioritizes the consequent results for the most influential challenge by using ANP model. The empirical results conclude that the security has the highest influence value i.e. 54% of the total measurement, while privacy and accuracy stand second and third among the most influential factors with 36% and 8% values respectively. Finally, the study provides important clues in the decision-making process in finding the solutions to such challenges faced by big data.