About the Journal

Aim

Journal of Confident Data and Business Management is an open access, quarterly, peer-reviewed journal publishing finest peer review research of theory and application of data science and data analytics across all fields of Business, Engineering, Science & Technology on the basis of its originality, significance, interdisciplinary interest, timeliness, accessibility and conclusions.

Journal of Confident Data and Business Management refers to the concept of using reliable, accurate, easy to use and well-analyzed data to make informed business decisions. In today’s fast-paced and data-driven world, decisions rely on data to drive strategies, optimize operations, improve performance, and achieve sustainable growth. Confidence in data ensures that users can trust the insights derived from it, leading to more effective decision-making.

The aim of “Journal of Confident Data and Business Management” is to serve and provide an advanced platform for researchers engaged with data-driven approaches to all areas as well as data science and analytics-related research and findings applicable to business studies and related topics.

Article Type

Journal of Confident Data and Business Management publishes following types of articles:

  • Research articles
  • Review articles (Authoritative and Comprehensive)
  • Mini review
  • Personal Account
  • Case study
  • Short notes

Scope/ Topics of Interest:

Journal of Confident Data and Business Management publish rigorously peer-reviewed original research and review articles. Topic of interest includes, (but not limited) to the following fields of research and will be considered for publication, upon satisfying accepted ethical and scientific publishing standards.

  • Data Collection and Data Acquisition
  • Data Mining & Data-intensive Computing
  • Business Analytics and Management
  • Internet of Things (IoT) and Data Modeling
  • Information Systems for Government Policy
  • Engineering Systems for Business Applications
  • Infrastructure Confident Systems
  • Collaborative and Confident Technologies
  • Confident Public Policy in Innovation
  • Finance, Insurance and Services Management
  • Privacy and Accountability in Data
  • Secure, Sustainable Data and Businesses
  • Interdisciplinary Applications of Data and Business