MBA in Business Analytics
Master of Business Administration (MBA) in Business Analytics is designed to equip students with a strong foundation in business strategy and management while honing their analytical skills. It focuses on data analysis, predictive modeling, and business intelligence, enabling professionals to derive insights from complex data and use them to inform business strategies and decisions.
This program is ideal for those looking to pursue careers in data analytics, consulting, marketing analytics, financial analysis, operations, and other data-driven roles in a business context.
Course Duration
- Duration: Typically 2 years (4 semesters).
- Some universities may offer accelerated or part-time programs with a 1-year duration or flexible options for working professionals.
Syllabus of MBA in Business Analytics
The MBA in Business Analytics course combines business administration with advanced data analytics techniques. The syllabus typically includes the following core and elective subjects:
A. Core Subjects
- Introduction to Business Analytics
- Overview of analytics in business, types of analytics, and the role of data in decision-making.
- Data Management and Data Warehousing
- Concepts of databases, data storage, and data retrieval techniques. Introduction to big data technologies.
- Statistical Methods for Business Analytics
- Descriptive and inferential statistics, regression analysis, probability theory, hypothesis testing.
- Predictive Analytics and Modeling
- Techniques like regression, classification, decision trees, and machine learning for predicting future trends.
- Data Visualization and Reporting
- Tools like Tableau, Power BI, and Excel for visualizing data and presenting findings in a clear and actionable way.
- Operations and Supply Chain Analytics
- Using analytics to optimize processes, manage inventory, and improve supply chain performance.
- Marketing Analytics
- Applying data analytics to marketing strategies, customer segmentation, pricing, and campaign effectiveness.
- Financial Analytics
- Techniques for analyzing financial data, forecasting, risk analysis, and investment analysis.
- Business Intelligence and Decision Support Systems
- Tools and technologies used to collect, analyze, and present business data for strategic decision-making.
- Ethical Issues in Data Analytics
- Understanding privacy, ethics, and governance in data analytics, and the importance of data security.
B. Elective Subjects
- Advanced Analytics Techniques (e.g., Artificial Intelligence, Natural Language Processing)
- Machine Learning for Business
- Text Mining and Sentiment Analysis
- Blockchain and Analytics
- Data Science in Business
C. Industry Projects / Internship
- Students are usually required to complete an internship with a company or work on a real-life project to apply their knowledge to actual business problems.