BUSINESS INTELLIGENCE (4 Credits)

Learning Outcomes:

On successful completion of this course, student will be able to: LO1 – explain the motivations, concepts, methods, and methodologies for decision support systems, business intelligence, and analytics; LO2 – recognize the new technology trends as the enablers of the modern-day business analytics and intelligence for decision support; LO3 – analyze how organizations employed business analytics and intelligence to make decisions or gain a competitive edge; LO4 – identify Decision Support Opportunities that are supported by business analytics and intelligence.

Topics:

1. Topics: Recognizing Types of Decision Support;
2. Using Big Data for Decision Support;
3. Business Intelligence and Data-Driven DSS;
4. Predictive Analytics and Model-Driven Decision Support;
5. Nature of Data, Statistical Modeling, and Visualization;
6. Data Mining Process, Methods, and Algorithms;
7. Text, Web, and Social Media Analytics;
8. Using Big Data for Decision Support;
9. Predictive Analytics and Model-Driven Decision Support;
10. Nature of Data, Statistical Modeling, and Visualization;
11. Data Mining Process, Methods, and Algorithms;
12. An overview of Business Intelligence, Analytics, Data Science, and AI;
13. Artificial Intelligence Concepts, Drivers, Major Technologies, and Business Applications;
14. Prescriptive Analytics: Optimization and Simulation;
15. AI-Based Trends in Analytics and Data Science;
16. Decision Support Benefits, Trade-Offs, and Opportunities;
17. Ethical, Privacy, and Managerial Considerations in Analytics;
18. Prescriptive Analytics: Optimization and Simulation;
19. Artificial Intelligence Concepts, Drivers, Major Technologies, and Business Applications.