Digital Intelligence (DI)
Tools and systems that help organizations gather, store, access and analyze data to support decision-making: business intelligence, analytics, data mining and data-driven business models.
- Data science and business intelligence – theoretical and practical aspects
- Data science and business intelligence applications and industry experience
- Business intelligence
- Business Model Innovation
- Business intelligence, digitization and data driven business models
- Business analytics and the new role of IT in enterprises
- Impacts of business analytics for the performance of profit or non-profit organizations
- Data warehousing, data mining, online analytical processing, and reporting capabilities
- Statistical analysis and characterization, predictive analytics and prescriptive analytics
- Process mining, pattern mining, and swarm intelligence
- Data quality assessment and improvement: preprocessing, cleaning, and missing data
- Semi-structured or unstructured data in BI systems
- Information integration for data and text mining
- Dynamic pricing: potentials and BI approaches
- Cloud-computing models and scalability in BI systems
- Mobile application, smart data, smart services, and smart products
- Data privacy and security issues in BI systems
- Digital marketing, new web services, semantic web and data analytics
- Analytics for healthcare and other public sectors
- Educational data mining
- Social network data analysis
- Web survey methods in business intelligence
- Organizational and human factors, skills, and qualifications for BI approaches
- Teaching BI approaches in academic and industrial environments
- Smart Talent Management
- Digital Learning & AI-Powered Upskilling