Journal of Applied Big Data Analytics, Decision-Making, and Predictive Modelling Systems

About

The Journal of Applied Big Data Analytics, Decision-Making, and Predictive Modelling Systems is a scholarly publication  that addresses the growing convergence between theoretical data science and practical implementation challenges faced by organizations across various sectors. This publication emerges from the recognition that while significant advances have been made in big data technologies and analytical methodologies, there remains a critical need for research that demonstrates how these innovations can be effectively translated into operational decision-making frameworks.

The journal's editorial mission reflects an understanding that modern data-driven organizations require more than just sophisticated analytical tools—they need comprehensive systems that can transform raw data into actionable insights while supporting complex decision-making processes. This perspective acknowledges that the value of big data analytics lies not merely in the technical capabilities of processing large datasets, but in the ability to create meaningful connections between analytical findings and strategic organizational outcomes.

In today’s data-centric world, where organizations increasingly rely on analytics to inform strategies and predict outcomes, the journal aims to play a role in disseminating best practices and novel methodologies. Topics of interest may include machine learning algorithms for predictive modeling, big data technologies for decision support, and case studies showcasing successful applications of analytics in industry settings.