Overview
In a rapidly evolving, data-driven business environment, executives must complement experience and intuition with evidence-based decision-making. This course equips leaders with tools and frameworks to transform raw data into meaningful insights that enhance strategic direction, operational efficiency, and sustainable growth. By linking business challenges with advanced analytics, participants will learn how to define problems clearly, apply rigorous analytical methods such as regression analysis, predictive modeling and optimization, and communicate results in ways that drive alignment and impact at the executive level.
Through a combination of case studies, simulations, and hands-on projects, the course emphasizes the practical use of descriptive, predictive, and prescriptive analytics, alongside emerging techniques in machine learning, and data visualization. Special attention is given to the ethical and responsible use of data, ensuring that executives not only generate value for their organizations but also build trust with stakeholders. Graduates will leave the course prepared to integrate analytics into strategy, shape data-informed organizational cultures, and lead with confidence in an era of digital transformation.
Outline
This course is divided into eight Lessons for the eight-week period:
- Lesson 1: Business Analytics, Analytics Strategy & Problem Framing
- Lesson 2: Data Understanding
- Lesson 3: Data visualization, Business reporting, and Information dashboards
- Lesson 4: Probability Distributions and Statistical Inference
- Lesson 5: Regression Analysis
- Lesson 6: Time Series Analysis
- Lesson 7: Machine Learning Basics- Classification, Clustering and Market Basket Analysis
- Lesson 8: Optimization and Decision Modeling
Learning outcomes
By the end of this course, students should be able to:
- Incorporate analytics into strategic and operational decision-making.
- Communicate analytical results effectively to diverse executive audiences.
- Discuss and distinguish the three main types of business analytics: descriptive, predictive, and prescriptive analytics.
- Generate business information reports, design dashboards and other data visualizations without coding.
- Perform basic predictive analytics with machine learning without coding.
Evaluation
Your grade will be based on the successful completion of two individual assignments, one mini project and on your participation in “think tank” questions on discussion forums.
| Activity | Weight |
| Assignment #1 | 20% |
| Assignment #2 | 30% |
| Assignment #3 | 30% |
| Participation in Weekly Discussions | 20% |
| Total | 100% |
To be successful in this course you must achieve the following:
- Receive an average of 60% on the participation component (that is, 12 out of the 20 marks available in total for participation in the Strategic Analytics and Critical Thinking Forum), and
- Receive an average of 60% over all course components (that is, the three organization assignments and participation in the Strategic Analytics and Critical Thinking Forum).
Materials
Digital course materials
Links to the following course materials will be made available in the course:
Albright, S. C., & Winston, W. L. (2024). Business analytics: Data analysis & decision making (8th ed.). Cengage Learning.
Davenport, T. H., & Harris, J. G. (2017). Competing on analytics: Updated, with a new introduction: The new science of winning (E-book ed.). Harvard Business Review Press.
- All other course materials will be accessed online.
- Software applications and tools: Power BI, Excel and R.