COURSE OUTLINE
Course Name: Introduction to Business Analytics
Course Code: D1UF301T
Programme
Academic Session
Semester
Instructor(s)
Credits
No of Sessions
Prerequisite
BBA (Business Analytics)
2024-2025
III
Dr Virender Kumar Dahiya
3
45
None
Course Overview
Analytics has become increasingly important in the business world as organizations have
access to vast amount of data. With businesses become increasingly digital, data is being
collected at an increasing rate. Customer databases, web logs, attitudinal surveys and
transactional databases, mobile phone activities, transportation and other data sources all
contribute to companies and organizations collecting and holding more data than ever before.
By exploiting this data, organizations are better able to make evidence-based decisions to
sustain continuous improvements and gain insights to inform critical business decisions.
This course gives a comprehensive knowledge to provide an overview of key areas of business
analytics: descriptive analytics, predictive analytics, prescriptive analytics, and their
application to real-world business practices. Business analytics skills are needed to transform
the data into actionable insights using mathematical and computer models. The needs of skills
in business analytics both nationally and globally have led organizations to an increasing need
in attracting and retaining people with business analytics skills.
Course Outcomes
After completing the course, students should be able to:
CO1
Define business analytics and understand its importance in decision making.
CO2
Apply at least one tool/technique of business analytics on analyzing data.
CO3
State some typical examples of business applications in which analytics would be
beneficial.
CO4
Formulate business analytics strategies based upon insight from data.
Course Content
Unit I: Introduction
9 lecture hours
Analytics: Business analytics, data analytics, and data science. Evolution of business analytics.
Using business analytics: key benefits; challenges faced by organizations. Tools/techniques for
business analytics. Types of business analytics. Data for business analytics.
Business analytics professionals: Application analyst, research analyst, and user analyst; key
skills for business analyst professionals.
Case study- 2018 saw a sharp increase in air crash deaths_visualizing and evaluating risk.
Unit II: Descriptive Analytics (Using MS Excel/Python/R)
9 lecture hours
Meaning, examples, and applications of descriptive analytics. Descriptive statistics: Frequency
distributions and histograms, Measures of location, dispersion, and association.
Data visualization: Tabular versus visual data. Tools and software for data visualization.
Creating charts. Dashboards.
Case study: Times are changing_the case of Movado Group
Unit III: Predictive Analytics (Using MS Excel/Python/R)
9 lecture hours
Meaning, examples, and applications of predictive analytics. Tools for building predictive
models: Trendlines, regression analysis. Forecasting techniques. Data Mining: Basic concepts,
approaches.
Case study: America’s major league soccer_artificial intelligence and the quest to become a
world class league.
Unit IV: Prescriptive Analytics (Using MS Excel/Python/R)
9 lecture hours
Meaning, examples, and applications of prescriptive analytics. Optimization models: Types,
Examples. Developing linear optimization model. Solving linear optimization model.
Transportation models. What-if analysis for optimization models.
Case study: VBK fibreo tech pvt ltd_product mix dilemma
Unit V: Decision Analysis and Applications of Business Analytics
9 lecture hours
Formulating decision problem. Decision Trees- structure and components. Utility and decision
making. Applications- Web analytics, marketing analytics, human resource analytics, supply
chain analytics.
Case study: Mentorrd EduTech_charting new territories through social media marketing.
Textbooks
1. Evans, J. R. (2020). Business analytics (3rd ed). Pearson Education Limited.
Reference Books
1. Kumar, U. D. (2021). Business analytics: The science of data driven decision making
(2nd ed). Wiley India.
2. Prasad, R. N. & Acharya, S. (2016). Fundamentals of Business Analytics (2nd ed.).
Wiley India.
3. Raj, S., (2015). Business Analytics. Cengage Learning.