The Setting and Course Description

Data, data everywhere! Data has gone from being scarce to super-abundant and the world today contains an unimaginably vast amount of digital information which is getting ever vaster, ever more rapidly. This makes it possible to do things that could not previously be done – spot business trends, prevent diseases, combat crime and so on. Managed well, data can be used to unlock new sources of economic value, provide fresh insights into scientific and technological challenges and even hold decision-makers to account. The ability to use data effectively to drive rapid, precise and profitable decisions has been a critical strategic advantage for companies as diverse as Walmart, Google, Capital One, Disney, Amazon, Uber and Flipkart.

Business analytics refers to ways in which enterprises such as businesses, non-profits and governments can use data to gain insights and make better decisions. Business analytics is applied in operations, marketing, finance, and strategic planning among other functions.

Course Objectives

This course is designed to provide a learning process to students in the handling of data and the tools required in managing them. The course sensitizes students on the use of data to lead to information; use of information and statistical and quantitative analysis to lead to enhanced decision making capabilities.

In this course, you will learn to identify, evaluate and capture business analytic opportunities that create value. This course emphasizes that business analytics is not a theoretical discipline – these techniques are interesting and important to the extent that they can be used to provide real insights and improve the speed, reliability and quality of decisions. The concepts learned in this class should help you identify opportunities in which business analytics can be used to improve performance and support important decisions.

Performance Objectives

At the end of this course, the student should have improved competencies and specific knowledge in:

  1. Understanding the emergence of business analytics as a competitive strategy

  2. Understanding a business problem and convert it into a BA model 

  3. The ability to think critically about data and the analyses based on those data based on

    1. Data visualization

    2. Decision making tools

    3. Advanced analytical tools to analyse problems under uncertainty

  4. Improved knowledge in data analysis tools such as Microsoft Excel and SPSS


Course Content

  1. Introduction to business analytics

    1. Business Analytics and Decision Making

    2. Data: sources and types

    3. Measures, Metrics, KPIs and Performance Management

  2. Descriptive Analytics

    1. Descriptive statistical measures

    2. Analytics using spreadsheets

  3. Data Visualization

  4. Data Warehousing and Data Mining

    1. Data preparation and imputation

    2. Data Mining

  5. Predictive Analytics

    1. Predictive Modeling

  6. Other topics

    1. Domain Specific Analytics

    2. Big data analysis

    3. Emerging Technologies



Lecture based, Group discussion, Case analysis, Lab Sessions, Assignments

Tools such as Microsoft Excel and SPSS will be used extensively during class.


Assignments / Lab                                                                  30 Marks

Mid-Term Exam                                                                      30 Marks

End-Term Exam                                                                      40 Marks

Total                                                                                        100 Marks


BOOKS (For reference purposes)

There is no specific text book for this class. Hand-outs will be provided in class for important topics.

PPTs of lectures will be distributed (as pdf files) after the respective class. PPTs will contain details on references and recommended readings for that particular lecture.