The SPC Journal of Data Science & Analytics (SPCJDSA) is an international, peer-reviewed, open-access journal dedicated to advancing the theory, methodologies, and applications of data science, analytics, and data-driven decision-making. The journal provides a global platform for researchers, data scientists, statisticians, analysts, and industry practitioners to publish high-quality original research articles, review papers, and applied case studies that transform data into actionable knowledge and insights. SPCJDSA covers a broad range of topics, including statistical learning, machine learning, data mining, big data technologies, predictive and prescriptive analytics, business intelligence, data visualization, natural language processing, time-series analysis, and domain-specific analytical applications. The journal is committed to fostering interdisciplinary collaboration across computer science, statistics, mathematics, engineering, business, healthcare, finance, and other applied fields. By promoting innovative analytical methods and real-world data applications, SPCJDSA aims to contribute significantly to scientific discovery, operational excellence, and evidence-based decision-making in an increasingly data-driven world.
The review process typically takes 4–8 weeks, depending on reviewer availability and the complexity of the manuscript. If accepted, the final version of the paper will be published online within 1–2 weeks and included in the next available issue. SPCJDSA maintains a selective peer-review process with an acceptance rate of approximately 25–30%, ensuring the publication of high-quality, methodologically rigorous, and impactful research contributions in the rapidly evolving fields of data science and analytics.
About the Journal
Title: SPC Journal of Data Science & Analytics
E-ISSN: Coming soon
The SPC Journal of Data Science & Analytics (SPCJDSA) is an international, peer-reviewed, open-access journal dedicated to advancing the theory, methodologies, and applications of data science, analytics, and data-driven decision-making. The journal provides a global platform for researchers, data scientists, statisticians, analysts, and industry practitioners to publish high-quality original research articles, review papers, and applied case studies that transform data into actionable knowledge and insights. SPCJDSA covers a broad range of topics, including statistical learning, machine learning, data mining, big data technologies, predictive and prescriptive analytics, business intelligence, data visualization, natural language processing, time-series analysis, and domain-specific analytical applications. The journal is committed to fostering interdisciplinary collaboration across computer science, statistics, mathematics, engineering, business, healthcare, finance, and other applied fields. By promoting innovative analytical methods and real-world data applications, SPCJDSA aims to contribute significantly to scientific discovery, operational excellence, and evidence-based decision-making in an increasingly data-driven world.
The review process typically takes 4–8 weeks, depending on reviewer availability and the complexity of the manuscript. If accepted, the final version of the paper will be published online within 1–2 weeks and included in the next available issue. SPCJDSA maintains a selective peer-review process with an acceptance rate of approximately 25–30%, ensuring the publication of high-quality, methodologically rigorous, and impactful research contributions in the rapidly evolving fields of data science and analytics.