About the Journal
Journal of Applied Big Data Analytics, Decision-Making, and Predictive Modelling Systems
About the Journal
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.
Policies
The journal upholds a set of policies designed to ensure the quality, integrity, and accessibility of its publications. These policies guide authors, reviewers, and editors in maintaining high standards:
Ethical Guidelines
Authors are required to adhere to strict ethical standards, particularly regarding data privacy, security, and the responsible use of big data. This includes ensuring that research respects individual rights, complies with legal standards, and mitigates potential biases in data-driven analyses.
Open Access
The journal operates under an open access model, making all published content freely available to the public. This policy enhances the visibility and impact of the research, enabling broader engagement from academics, industry professionals, and policymakers worldwide.
Submission Guidelines
Authors must follow Polar formatting and documentation requirements, such as providing detailed methodologies and data sources. These standards ensure consistency, clarity, and transparency in published works, making it easier for readers to understand and evaluate the research.
Reproducibility
To promote transparency and scientific rigor, the journal encourages authors to share datasets and code whenever possible. This practice allows other researchers to verify findings, replicate studies, and build upon existing work, fostering a collaborative research environment.
Peer Review Process
The journal employs a rigorous peer review process to ensure the quality, validity, and relevance of its publications. This process involves several key steps:
Expert Reviewers
Each submission is evaluated by experts in big data analytics, decision-making, or predictive modeling. These reviewers bring specialized knowledge to assess the technical accuracy and significance of the work.
Evaluation Criteria
Reviewers assess manuscripts based on key criteria, including originality, methodological rigor, contribution to the field, and clarity of presentation. This ensures that published articles offer meaningful advancements or insights.
Multiple Rounds of Review
The peer review process may involve multiple rounds of feedback and revision. Authors are expected to address reviewer comments and refine their work to meet the journal’s high standards before publication.
Editorial Oversight
The journal’s editorial board, composed of distinguished experts in the field, oversees the review process and makes final publication decisions. Their expertise ensures that only the highest-quality research is accepted.
The Journal of Applied Big Data Analytics, Decision-Making, and Predictive Modelling Systems is a resource for those engaged in the practical applications of big data analytics. Through its focus on ethical research practices, open access dissemination, and a thorough peer review process, the journal upholds a commitment to publishing impactful, high-quality research that advances the field and supports data-driven innovation.