Aims & Scope

The journal aims to advance research and practice at the intersection of data science, big data technologies, and real-world applications. It provides a platform for scholarly work addressing the integration of cutting-edge data analytics into business intelligence, machine learning models, data visualization, cybersecurity, data governance, and AI-driven decision-making strategies. The journal welcomes theoretical, empirical, and application-oriented studies that contribute to the understanding and advancement of technological innovation in data science and big data across diverse global industries and environments.

Single-blinded Peer Review

Committed to scientific integrity and editorial excellence, Data Science & Big Data Technology employs a single-blinded peer-review process and adheres to the highest ethical standards as outlined by COPE. The journal embraces transparency, reproducibility, and accessibility, ensuring that all published content is freely available under an open-access model to maximize dissemination and global impact.

ISSN

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Abstracting & Indexing

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