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.
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.
At the end of this course, the student should have improved competencies and specific knowledge in:
Understanding the emergence of business analytics as a competitive strategy
Understanding a business problem and convert it into a BA model
The ability to think critically about data and the analyses based on those data based on
Decision making tools
Advanced analytical tools to analyse problems under uncertainty
Improved knowledge in data analysis tools such as Microsoft Excel and SPSS
Introduction to business analytics
Business Analytics and Decision Making
Data: sources and types
Measures, Metrics, KPIs and Performance Management
Descriptive statistical measures
Analytics using spreadsheets
Data Warehousing and Data Mining
Data preparation and imputation
Domain Specific Analytics
Big data analysis
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.
- Teacher: Josephine Gemson Dr.