Business Data Management
A course providing a foundational understanding of how businesses are organized and run from a data perspective, using case studies across multiple industries.
This course was designed to bridge the gap between data science and practical business application. It began by establishing a strong foundation in the micro-economic principles that govern business operations, from consumer demand to firm-level strategy and industry analysis. The core of the course was a series of immersive, data-driven case studies that spanned major industries: E-Commerce (Fabmart), Manufacturing (Ace Gears), IT/HR (Tech Enterprises), and FinTech (PayBuddy). Through these cases, I learned how to analyze real-world business data to tackle challenges in sales forecasting, inventory management, production scheduling, HR analytics, and targeted marketing using A/B testing.
Instructors
- Prof. G Venkatesh, Director, School of Technology at Dhirubhai Ambani University
- Prof. Suresh Babu M, Department of Humanities and Social Sciences, IIT Madras
- Dr. Milind Gandhe, Chief Programme Officer, MINRO COE, IIIT Bangalore
Course Schedule & Topics
The course is structured around foundational business concepts and a series of in-depth, industry-specific case studies.
| Week(s) | Primary Focus | Key Topics Covered |
|---|---|---|
| 1 | Foundations of Business Economics | Micro & Macro economics, consumption, production, exchange, and consumer survey data. |
| 2 | Micro-economic Concepts | Utility, indifference curves, demand/supply, elasticity, and production cost analysis. |
| 3 | Firm-Level Strategy & Performance | Pricing strategies, analysis of firm performance using key financial ratios. |
| 4 | Industry-Level Data Analysis | Industry classification, IIP/PMI, market concentration, and Porter’s five forces. |
| 5-6 | Case Study: E-Commerce (Fabmart) | Revenue/volume pareto, trend analysis, inventory management, and avoiding stockouts. |
| 7-8 | Case Study: Manufacturing (Ace Gears) | Revenue analysis, production scheduling, scrap analysis, and raw material re-ordering. |
| 9 | Case Study: IT & HR (Tech Enterprises) | HR analytics, internal sourcing, recruitment channel analysis, and onboarding. |
| 10-11 | Case Study: FinTech (PayBuddy) | Payment processing, targeted marketing, A/B testing analysis, and credit risk evaluation. |
| 12 | Course Wrap-up & Projects | Summary of case studies and discussion on student-acquired data sets for project work. |
Material used
- All case studies, datasets, and reading materials were provided through the course portal.