Curriculum Guideline

Fundamentals of Business Analytics

Effective Date:
Course Code
CSIS 3360
Fundamentals of Business Analytics
Computing Studies & Information Systems
Commerce & Business Administration
Start Date
End Term
Semester Length
Max Class Size
Contact Hours
Lecture: 2 hours per week Seminar: 2 hours per week Total: 4 hours per week
Method Of Instruction
Methods Of Instruction

Lecture, seminar and hands-on exercises in the lab

Course Description
Business analysts who can leverage data to help a company make the right decisions are highly sought after. This hands-on course will introduce the fundamental concepts and tools needed to understand the emerging role of business analytics within organizations. Students will be required to work with real-world examples using current computing tools. Integral to the course is a group project where students will complete a variety of tasks including: requirement elicitation; developing hypothesis; data exploration; dimensional analysis; identifying metrics; and visual presentation of results. Emerging topics such as predictive analytics, web analytics and processing of semi-structured data will also be discussed.
Course Content
  1. Intro to Business Analytics and Business Analyst role
  2. Applications of Business Analytics
  3. Dimensional Analysis intro
  4. Dimensional Analysis – 7W technique
  5. Inference, Hypothesis Testing
  6. Regression
  7. Forecasting
  8. Data visualization: discussion on various chart types and a look at data visualization gone wrong.
  9. Requirement analysis: Don’t gather, Elicit requirements
  10. Predictive analytics and its role in decision making
  11. Designing dashboards and using the right metrics
  12. Web analytics / semi-structured data discussion
  13. Project presentations
Learning Outcomes
  1. Describe the domain of Business Analytics and the role of Business Analyst;
  2. Give examples of different applications of Business Analytics across different industries;
  3. Develop a dimensional model for a given Business Analytics project;
  4. Carry out hypothesis testing to support a decision;
  5. Apply correlation and regression analysis to classify related variables;
  6. Prepare forecasts using time series analysis;
  7. Describe proper use of data visualization tools and chart types;
  8. Demonstrate requirement elicitation techniques such as interviewing, facilitation, prototyping;
  9. Discuss the emerging field of predictive analytics;
  10. Identify vain vs real business metrics;
  11. Evaluate components to be included in executive dashboards;
  12. Explain the growing field of Web analytics and semi-structured data;
  13. Illustrate the familiarity with using the current analytics tools such as MS Excel, R, SAS.
Means of Assessment

Class Participation

5% - 10%

Quizzes (Best 5 out of 8 @ 3% each)


Proposal (to implement Business Analytics)

5% - 15%

Group Project

15% - 25%

Midterm Examination

20% - 30%

Final Examination

20% - 30%


Textbook Materials

Instructor compiled materials


other textbooks as approved by the department


CSIS 2200 AND (BUSN 2429 or MATH 1160)

(Note: CSIS 2300 is recommended)