Joint Certificate Program in Business Intelligence and Analytics

This program equips students with contemporary skills and knowledge in business intelligence and analytics using SAS software. The program consists of four courses offered by the Department of Decision and Information Sciences. Candidate courses (and their use of SAS software) are listed below:

STAT 301 Business Statistics

This course provides a survey of statistical topics useful in support of managerial decision-making. The course covers sampling and sampling distributions; foundational statistical inference, including one- and two-sample tests for means and proportions; confidence interval estimation and hypothesis testing; chi-square test; regression analysis; and computer applications. The course has a heavily applied emphasis.

  • Software: SAS Enterprise Guide
  • Prerequisite: Introduction to Business Statistics

BSAN 383 Business Intelligence

This course introduces the concept of Business Intelligence (BI). Students will learn how BI is used by organizations to make better business decisions, use fewer resources, and improve the bottom line. This course provides an overview of business intelligence topics as well as hands-on experiences. Topics include business analytics, data visualization, data mining, data warehousing and business performance management.

  • Software: SAS Visual Analytics
  • Prerequisite: Introduction to Management Information Systems

STAT 440 Business Forecasting

This course introduces time-series forecasting techniques to support trend forecasting and business cycles. Contemporary techniques such as moving average, exponential smoothing, ARIMA, and Box-Jenkins method are introduced. Software tools including spreadsheet and analytics systems are used. A course project is required.

  • Software: SAS Enterprise Guide
  • Prerequisite: Business statistics

BSAN 465 Predictive Analytics

This course provides an introduction to predictive analytics techniques used in business applications and social science research. Using enterprise-class analytics software and real-world data, students will learn how to build predictive models using techniques such as logistic regression, neural networks, cluster analysis, and decision trees. A course project is required.

  • Software: SAS Enterprise Miner
  • Prerequisite: Business Statistics

BSAN 480 Social Media Analytics

This course introduces the technologies and managerial issues related to social media analytics (SMA). Students will learn the importance of social media in influencing the reputation of contemporary businesses, examine text mining, sentiment analysis, and social network analysis, and apply the concepts, techniques, and tools to analyzing social media data. Real-world data such as online reviews, microblog postings, human interaction networks, and business networks will be studied. Hands-on training will be provided.

  • Software: SAS Text Miner
  • Prerequisite: Business Statistics