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Journal Photo for INTERNATIONAL JOURNAL OF BUSINESS AND DATA ANALYTICS
Peer reviewed only Open Access

INTERNATIONAL JOURNAL OF BUSINESS AND DATA ANALYTICS (IJBDA)

Publisher : IAEME Publication
Big Data Predictive Analytics Data Mining
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e-ISSN 1166-1544
Issue Frequency Monthly
Impact Factor 3.00
Est. Year 2025
Mobile 9884798314
Language English
APC YES
Impact Factor Assignee Google Scholar
Email editor@iaeme.com

Journal Descriptions

The aim of the INTERNATIONAL JOURNAL OF BUSINESS AND DATA ANALYTICS (IJBDA) is to serve as a pivotal platform within the realm of Business Analytics and related fields. It aims to facilitate the exchange of innovative ideas, cutting-edge research, and practical applications in the dynamic domain of data analytics within business management. The journal endeavors to bridge interdisciplinary gaps, fostering a pragmatic, application-driven approach that enables practitioners and academics to harness synergies among traditionally diverse domains for informed decision-making. Scope The scope of the INTERNATIONAL JOURNAL OF BUSINESS AND DATA ANALYTICS (IJBDA) encompasses providing an inclusive forum for the exchange of innovative ideas, cutting-edge research, and practical applications in the domain of data analytics within business management. It aims to facilitate collaborations and discussions among researchers, practitioners, IT professionals, software developers, and vendors from diverse organizational spheres. The journal encourages the exploration and dissemination of various models, methodologies, processes, and principles, emphasizing their practical and actionable implementations. IJBDA seeks to publish high-quality research contributions, case studies, and innovative ideas that significantly contribute to the evolution of analytics theory and practice within the dynamic context of business management.

INTERNATIONAL JOURNAL OF BUSINESS AND DATA ANALYTICS (IJBDA) is :-

  • International, Peer-Reviewed, Open Access, Refereed, Big Data, Predictive Analytics, Data Mining, Prescriptive Analytics, Business Process Optimization, Business Intelligence, Quantitative Methods, Decision Support Systems (DSS), Machine Learning in Business, Marketing Analytics, Management Analytics, Business Statistics, Data Visualization, Risk Management Analytics , Online , Monthly Journal

  • UGC Approved, ISSN Approved: P-ISSN E-ISSN: 1166-1544, Established: 2025, Impact Factor: 3.00
  • Does Not Provide Crossref DOI

  • Not indexed in Scopus, WoS, DOAJ, PubMed, UGC CARE

Indexing