CIS 3710 – Sample course syllabus

Title Business Intelligence
Description This course focuses on business intelligence – an information technology approach to data collection and data analysis to support a wide variety of organizational priorities, from performance evaluation to trend spotting and policy making. Students learn analytical components and technologies used to create dashboards and scorecards, data/text/Web mining methods for trend and sentiment analysis, and artificial intelligence techniques used to develop intelligent systems for decision support.
Prerequisites CIS 2200
Learning Goals At the completion of this course, students should be able to:

  • Articulate modern concepts, theories, and research in the field of Business Intelligence (BI).
  • Discuss how technologies that enable BI can be applied in organizational settings.
  • Discuss the various BI practices including knowledge integration, sourcing and managing BI solutions.
  • Discuss the social and ethical issues related to the use of Business Intelligence technologies in organizations.
  • Describe the various careers that relate to Business Intelligence.
Grades
ACTIVITY WEIGHTS
CASE DISCUSSIONS & ANALYSIS 4%
CHAPTER DISCUSSIONS 10%
WARM-UP ASSIGNMENT 1%
NEWSWORTHY 2%
INDIVIDUAL RESEARCH 2%
GROUP PROJECT
            GROUP REPORT 10%
            INDIVIDUAL PRESENTATIONS 3%
QUIZZES 4%
EXAMS
Mid-term #1 12%
Mid-term #2 20%
Mid-term #3 32%
TOTAL 100%
Textbooks Business Intelligence and Analytics. Systems for Decision Support, 10th Edition. R. Sharda, D. Delen, & E. Turban; Pearson/Prentice Hall, © 2015. ISBN-13: 978-0-13-305090-5, ISBN-10: 0-13-305090-4
Topics

Overview of BI and analytics

Foundation and Technologies for decision Making

Introduction to Tableau

Descriptive Analytics – Data warehousing

Predictive Analytics – Data Mining

Predictive Analytics – Text Analytics and Text Mining

Predictive Analytics – Web Analytics and Web Mining

Model Based Decision Making

Modeling and Analysis

Knowledge Management and Collaborative Systems

Big Data and Analytics

Business Analytics: Emerging Trends and Future Impacts