
MSc. in Data and Business Administration bridges the gap between data science and strategic business management, offering a uniquely integrated approach to developing data-driven leaders. This interdisciplinary program combines the power of data analytics, business intelligence, and statistical modeling with a solid understanding of modern business operations. The curriculum includes topics such as data visualization, predictive analytics, financial modeling, operations research, digital marketing analytics, and decision sciences, empowering students to make informed business decisions based on data. Using tools like Python, R, SQL, Excel, Tableau, and cloud-based platforms, students work on real-time business problems, develop dashboards, and interpret large datasets to uncover actionable insights.
The program is ideal for graduates from business, economics, IT, or engineering backgrounds who wish to work at the intersection of analytics and management. Career opportunities span across diverse industries, with job roles such as Business Analyst, Data Consultant, BI Specialist, Strategy Analyst, and Data-Driven Project Manager. With the growing global emphasis on data-centric decision-making, graduates are highly valued in sectors like finance, retail, logistics, consulting, and technology.

| S. No. | Course Work - Subject Area | Break Down of Credits |
|---|---|---|
| 1 | Data and Business Analytics Core | 19 |
| 2 | Data and Business Analytics Electives | 12 |
| 3 | Skill Enhancement Core | 27 |
| 4 | Value Added Core | 2 |
| 5 | Capstone Project/Dissertation | 20 |
| Total Credit | 80 |
| Course Codes | Courses | L | T | P | Credits | Type |
|---|---|---|---|---|---|---|
| 25M31CA111 | Business Analytics using R | 2 | 0 | 0 | 2 | SEC |
| 25M35CA111 | Business Analytics using R (Lab) | 0 | 0 | 2 | 2 | SEC |
| 25M31CA112 | Business Statistics using Excel | 2 | 0 | 0 | 2 | SEC |
| 25M35CA112 | Business Statistics using Excel (Lab) | 0 | 0 | 2 | 2 | SEC |
| 25M31CA113 | Data Mining Tools & Techniques | 3 | 1 | 0 | 4 | PCC |
| 25M31CA114 | Design Thinking and Innovation | 2 | 0 | 0 | 2 | PCC |
| 25M31CA115 | Business Communication | 3 | 0 | 0 | 3 | SEC |
| 25M31CA116 | Introduction to Data Science | 3 | 0 | 0 | 3 | PCC |
| Total Credits | 20 |
| Course Codes | Courses | L | T | P | Credits | Type |
|---|---|---|---|---|---|---|
| XXXXXXXXX | Research Methods in Business | 3 | 1 | 0 | 4 | PCC |
| XXXXXXXXX | Big Data and Data Visualization | 1 | 0 | 0 | 1 | SEC |
| XXXXXXXXX | Big Data and Data Visualization (Lab) | 0 | 0 | 2 | 2 | SEC |
| XXXXXXXXX | Data Management using SQL | 2 | 0 | 0 | 2 | SEC |
| XXXXXXXXX | Data Management using SQL (Lab) | 0 | 0 | 2 | 2 | SEC |
| XXXXXXXXX | Digital Technology and Strategic Management | 3 | 0 | 0 | 3 | PCC |
| XXXXXXXXX | Elective 1 | 3 | 0 | 0 | 3 | PEC |
| XXXXXXXXX | Elective 2 | 3 | 0 | 0 | 3 | PEC |
| Total Credits | 20 |
| Course Codes | Courses | L | T | P | Credits | Type |
|---|---|---|---|---|---|---|
| XXXXXXXXX | Data Analytics using Python | 2 | 0 | 0 | 2 | SEC |
| XXXXXXXXX | Data Analytics using Python (Lab) | 0 | 0 | 1 | 1 | SEC |
| XXXXXXXXX | Predictive Analytics | 2 | 1 | 0 | 3 | PCC |
| XXXXXXXXX | Employability Skills | 2 | 0 | 0 | 2 | VAC |
| XXXXXXXXX | Elective 3 | 3 | 0 | 0 | 3 | PEC |
| XXXXXXXXX | Elective 4 | 3 | 0 | 0 | 3 | PEC |
| XXXXXXXXX | Corporate Internship | 6 | SEC | |||
| Total Credits | 20 |
| Course Codes | Courses | L | T | P | Credits | Type |
|---|---|---|---|---|---|---|
| XXXXXXXXX | Capstone Project/Dissertation | 0 | 0 | 0 | 12 | Project |
| XXXXXXXXX | Term Paper | 0 | 0 | 0 | 8 | |
| Total Credits | 20 | |||||
| Total Program Credits | 80 |

