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MBA in Business Analytics at Gautam Buddha University
Gautam Budh Nagar, Uttar Pradesh
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About the Specialization
What is Business Analytics at Gautam Buddha University Gautam Budh Nagar?
This MBA Business Analytics program at Gautam Buddha University focuses on equipping future managers with data-driven decision-making skills. It integrates core business principles with advanced analytical techniques, addressing the growing demand for professionals who can leverage big data for strategic insights in the Indian industry. The program emphasizes practical application and industry relevance.
Who Should Apply?
This program is ideal for fresh graduates from diverse backgrounds seeking entry into the high-growth field of data analytics in business, especially in India. It also suits working professionals looking to upskill in analytics or career changers transitioning to roles requiring data expertise. Candidates with a strong quantitative aptitude and a desire to solve complex business problems are well-suited.
Why Choose This Course?
Graduates of this program can expect to secure roles such as Business Analyst, Data Analyst, Financial Analyst, Marketing Analyst, or Operations Analyst in India. Entry-level salaries typically range from INR 4-8 LPA, with significant growth potential up to INR 15-25 LPA or more with experience. The program aligns with certifications like Tableau, Power BI, and various machine learning platforms.
Student Success Practices
Foundation Stage
Strengthen Quantitative & Statistical Foundations- (Semester 1-2)
Focus diligently on subjects like Business Statistics and Business Research Methods. Leverage online resources such as Coursera or NPTEL for additional practice in probability, hypothesis testing, and regression analysis. This forms the bedrock for advanced analytical techniques crucial for data science roles in India.
Tools & Resources
Coursera, NPTEL, Khan Academy
Career Connection
A solid quantitative foundation is critical for excelling in technical interviews and for building robust analytical models required by Indian data-driven organizations.
Master Business Domain Knowledge- (Semester 1-2)
Actively participate in discussions and case studies across core MBA subjects (Marketing, Finance, HR, Operations). Engage with business newspapers and magazines (e.g., Economic Times, Business Standard) to understand Indian industry dynamics. A strong understanding of business functions is key to applying analytics effectively.
Tools & Resources
Economic Times, Business Standard, Harvard Business Review cases
Career Connection
Bridging the gap between data and business context makes you a more valuable asset, allowing you to identify relevant problems and present actionable insights to Indian management.
Develop Foundational Software Skills- (Semester 1-2)
Become proficient in MS Excel for data cleaning, basic analysis, and visualization, along with introductory statistical software like R or Python from lab courses. Participate in online tutorials on platforms like GeeksforGeeks or DataCamp to build strong programming basics, highly valued by Indian employers.
Tools & Resources
MS Excel, R Studio, Python (Anaconda), GeeksforGeeks, DataCamp
Career Connection
Proficiency in these foundational tools is a primary requirement for most entry-level data and business analyst positions in India, enabling efficient data handling.
Intermediate Stage
Deep Dive into Core Analytics Tools & Concepts- (Semester 3)
Dedicate significant time to understanding Database Management Systems, Big Data Analytics, and Data Visualization tools (Tableau/Power BI). Work on projects and assignments beyond the classroom to gain hands-on experience. Mastering these tools is directly relevant to most business analytics roles in India.
Tools & Resources
SQL, Hadoop ecosystem (e.g., Apache Spark), Tableau, Power BI, Kaggle
Career Connection
Demonstrable expertise in these industry-standard tools makes you highly marketable for Business Intelligence and Data Analyst roles across Indian sectors like IT, finance, and retail.
Engage in a Meaningful Summer Internship- (After Semester 2 (during summer break))
Actively seek out and secure an internship in a relevant industry role (e.g., data analyst intern, business intelligence intern). Focus on solving real-world business problems using the analytical skills acquired. This practical exposure is invaluable for gaining industry insights and improving placement chances in the Indian job market.
Tools & Resources
LinkedIn Jobs, Internshala, University Placement Cell
Career Connection
Internships provide crucial practical experience, a strong resume builder, and often lead to pre-placement offers, accelerating your career in the competitive Indian job market.
Build a Professional Network- (Semester 3)
Attend workshops, webinars, and industry events related to business analytics, both on-campus and online. Connect with faculty, alumni, and industry professionals on platforms like LinkedIn. Networking can open doors to mentorship, collaborative projects, and future job opportunities in India.
Tools & Resources
LinkedIn, Industry conferences (e.g., NASSCOM events), Alumni groups
Career Connection
A strong professional network is vital for career growth, providing insights, referrals, and access to unadvertised job openings within the Indian business analytics ecosystem.
Advanced Stage
Master Advanced Analytical Techniques- (Semester 4)
Focus intensively on Artificial Intelligence and Machine Learning for Business, applying these concepts through hands-on projects. Explore advanced topics in Marketing, Financial, and HR Analytics through specialized electives and certifications. This deep expertise positions graduates for high-impact roles in AI/ML driven companies in India.
Tools & Resources
Python libraries (Scikit-learn, TensorFlow, Keras), AWS/Azure/GCP ML platforms, Udemy/Coursera advanced courses
Career Connection
Proficiency in AI/ML is highly sought after by Indian companies for roles like Data Scientist and Machine Learning Engineer, offering higher earning potential and career progression.
Undertake a Comprehensive Research Project- (Semester 4)
Choose a compelling business problem for the Research Project, applying end-to-end analytical methodologies from data collection to model deployment and insight generation. Aim to publish findings or present at conferences, demonstrating research capability and problem-solving skills to potential Indian employers.
Tools & Resources
Jupyter Notebook, Google Scholar, Plagiarism checkers
Career Connection
A well-executed research project showcases your ability to conduct independent analysis, a key differentiator in Indian hiring for strategic and research-oriented analytics roles.
Prepare for Placements Strategically- (Semester 4)
Develop a strong portfolio of projects showcasing analytical skills. Practice technical interviews, aptitude tests, and case study rounds common in Indian recruitment processes. Leverage the university''''s placement cell and alumni network to target relevant companies and roles, ensuring career readiness.
Tools & Resources
Resume/CV builders, InterviewBit, Glassdoor, University Placement Cell
Career Connection
Strategic preparation ensures you are well-equipped to navigate the competitive Indian job market, leading to successful placements in desired analytics roles.
Program Structure and Curriculum
Eligibility:
- Graduate (10+2+3) in any discipline with a minimum of 50% aggregate marks (45% for SC/ST category) or equivalent grade from a recognized Indian or foreign University.
Duration: 2 years (4 semesters)
Credits: 102 Credits
Assessment: Internal: 30%, External: 70%
Semester-wise Curriculum Table
Semester 1
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MBB-101 | Principles and Practices of Management | Core | 4 | Management Concepts, Planning and Decision Making, Organizing and Staffing, Directing and Motivation, Controlling and Ethics |
| MBB-102 | Managerial Economics | Core | 4 | Demand and Supply Analysis, Production and Cost Analysis, Market Structures and Pricing Decisions, Macroeconomic Environment, Business Cycles and Policies |
| MBB-103 | Business Statistics | Core | 4 | Descriptive Statistics, Probability Distributions, Sampling and Estimation, Hypothesis Testing, Correlation and Regression |
| MBB-104 | Accounting for Management | Core | 4 | Financial Accounting Principles, Cost Accounting Concepts, Management Accounting Tools, Financial Statement Analysis, Budgeting and Variance Analysis |
| MBB-105 | Information Systems for Business | Core | 4 | Fundamentals of Information Systems, IT Infrastructure and Architectures, Database Management, E-commerce and Digital Business, Enterprise Systems and ERP |
| MBB-106 | Business Communication | Core | 2 | Communication Process and Barriers, Oral Communication Skills, Written Business Communication, Presentation Techniques, Intercultural Communication |
| MBB-107 | Computer Lab (MS Office) | Lab | 2 | MS Word for Document Creation, MS Excel for Data Analysis, MS PowerPoint for Presentations, Advanced Excel Functions, Office Automation Tools |
Semester 2
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MBB-201 | Organizational Behaviour | Core | 4 | Foundations of Individual Behavior, Motivation Theories, Group Dynamics and Teamwork, Leadership and Power, Organizational Culture and Change |
| MBB-202 | Marketing Management | Core | 4 | Marketing Environment and Strategy, Consumer and Business Markets, Product Life Cycle and Branding, Pricing Strategies, Promotion and Distribution Channels |
| MBB-203 | Financial Management | Core | 4 | Financial Goals and Environment, Time Value of Money, Capital Budgeting Decisions, Working Capital Management, Capital Structure and Dividend Policy |
| MBB-204 | Human Resource Management | Core | 4 | HR Planning and Job Analysis, Recruitment and Selection, Training and Development, Performance Management, Compensation and Industrial Relations |
| MBB-205 | Operations Management | Core | 4 | Introduction to Operations Management, Process Design and Layout, Inventory Management, Quality Management and Control, Supply Chain Management |
| MBB-206 | Business Research Methods | Core | 4 | Research Design and Types, Data Collection Methods, Sampling Techniques, Data Analysis and Interpretation, Report Writing and Ethics |
| MBB-207 | Computer Lab (Statistical Software) | Lab | 2 | Introduction to Statistical Software (R/Python/SPSS), Data Import and Manipulation, Descriptive Statistics using Software, Inferential Statistics using Software, Data Visualization in Software |
Semester 3
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MBB-301 | Business Analytics | Core | 4 | Introduction to Business Analytics, Descriptive and Predictive Analytics, Prescriptive Analytics and Optimization, Data Mining Techniques, Big Data Concepts |
| MBB-302 | Database Management System | Core | 4 | Relational Database Concepts, SQL Querying and Manipulation, Data Warehousing and Data Marts, ETL Processes, NoSQL Databases Introduction |
| MBB-303 | Big Data Analytics | Core | 4 | Big Data Ecosystem (Hadoop, Spark), Distributed File Systems (HDFS), MapReduce Framework, Data Stream Processing, Cloud-based Big Data Solutions |
| MBB-304 | Data Visualization | Core | 4 | Principles of Data Visualization, Data Storytelling, Interactive Dashboards (Tableau/Power BI), Chart Selection and Design, Geospatial and Network Visualization |
| MBB-305 | Business Analytics Lab | Lab | 2 | Practical Application of Analytics Tools, Data Cleaning and Preprocessing, Predictive Model Building, Business Case Study Analysis, Dashboard Creation and Reporting |
| MBB-306 | Summer Internship Project | Project | 4 | Industry Problem Identification, Data Collection and Analysis, Solution Design and Implementation, Report Writing, Project Presentation |
| MBB-OEI-XX | Open Elective - I | Elective | 3 |
Semester 4
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MBB-401 | Artificial Intelligence and Machine Learning for Business | Core | 4 | Fundamentals of AI and ML, Supervised Learning (Regression, Classification), Unsupervised Learning (Clustering), Deep Learning Basics, ML Application in Business |
| MBB-402 | Marketing Analytics | Core | 4 | Customer Analytics and Segmentation, Web and Social Media Analytics, Campaign Effectiveness Measurement, Pricing Analytics, Predictive Modeling in Marketing |
| MBB-403 | Financial Analytics | Core | 4 | Risk Analytics and Management, Portfolio Optimization, Fraud Detection Techniques, Algorithmic Trading Strategies, Financial Forecasting |
| MBB-404 | HR Analytics | Core | 4 | Workforce Planning and Optimization, Employee Turnover Prediction, Performance and Engagement Analytics, Recruitment and Retention Analytics, Compensation and Benefits Analytics |
| MBB-405 | Research Project | Project | 8 | Problem Definition and Literature Review, Research Methodology and Design, Data Collection and Analysis, Results Interpretation and Discussion, Report Writing and Presentation |
| MBB-OEII-XX | Open Elective - II | Elective | 3 |
