About the Journal
Journal of Data Processing and Business Analytics (JoDPBA) is a double blind peer-reviewed, bi-annual journal, which aims to provide readers with the most recent findings in the field of data processing and business analytics. Each paper accepted for publication in the journal have a significant empirical or theoretical contribution. The journal welcomes research articles in all areas of computer science-related submissions.
JoDPBA aims to provide a platform for researchers, practitioners, and professionals to exchange innovative ideas, theories, methodologies, and practical applications in the areas of data processing, data mining, data visualization, statistical modeling, machine learning, and business analytics. The scope of the journal encompasses a wide range of industries and sectors, including but not limited to finance, marketing, healthcare, supply chain management, and e-commerce. The journal seeks to promote interdisciplinary collaboration and foster a deeper understanding of the role of data processing and business analytics in driving evidence-based decision-making, optimizing operations, improving organizational performance, and achieving competitive advantage in the digital era.
Focus and Scope:
- Batch and Real-time Processing
- Big Data Analytics
- Business Analytics
- Customer, Marketing, Financial and Operations Analytics
- Data Aggregation and Summarization
- Data Governance and Compliance
- Data Integration
- Data Mining and Machine Learning
- Data Processing Techniques
- Data Security and Privacy
- Data Storage and Retrieval
- Data Transformation and Integration
- Data Validation and Quality Assurance
- Data Visualization and Communication
- Data-Driven Decision Making
- Descriptive Analytics
- Performance Measurement and Metrics
- Predictive and Prescriptive Analytics
- Scalability and Performance Optimization
- Statistical Modeling and Analysis
