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MBA in Business Analytics at Galgotias University
Gautam Buddh Nagar, Uttar Pradesh
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About the Specialization
What is Business Analytics at Galgotias University Gautam Buddh Nagar?
This MBA in Business Analytics program at Galgotias University focuses on equipping future business leaders with data-driven decision-making skills. Given India''''s rapid digital transformation, there''''s immense relevance in leveraging analytical insights across sectors like e-commerce, finance, and healthcare. This program distinguishes itself by integrating core management principles with advanced analytical tools and techniques. The Indian market exhibits a strong demand for professionals who can translate complex data into actionable business strategies.
Who Should Apply?
This program is ideal for recent graduates across diverse disciplines, including B.Tech, B.Com, BBA, and BCA, who seek an entry point into the dynamic field of data science within a business context. It also caters to working professionals from various industries looking to upskill their analytical capabilities or pivot into roles demanding data expertise. Individuals with a keen interest in statistics, problem-solving, and technology, aiming for leadership roles in data-intensive environments, will find this program highly beneficial.
Why Choose This Course?
Graduates of this program can expect to pursue lucrative India-specific career paths such as Business Analyst, Data Scientist, Marketing Analyst, Financial Modeler, and Consultant. Entry-level salaries typically range from INR 4-7 lakhs per annum, with experienced professionals earning INR 15+ lakhs, demonstrating significant growth trajectories in Indian and multinational companies operating in India. The curriculum aligns with requirements for professional certifications like Tableau Specialist, AWS Certified Data Analytics, and relevant R/Python certifications.
Student Success Practices
Foundation Stage
Master Business Fundamentals and Foundational Statistics- (Semester 1-2)
Focus intently on core MBA subjects like Management Concepts, Financial Accounting, Marketing, and especially Business Statistics. Develop a strong understanding of statistical concepts, probability, and basic data interpretation, as these form the bedrock for advanced analytics. Actively participate in case studies and group discussions to apply theoretical knowledge to real-world business scenarios.
Tools & Resources
Khan Academy, Coursera (e.g., ''''Business Statistics and Analysis Specialization''''), Financial newspapers (Economic Times, Livemint)
Career Connection
A solid understanding of business functions and statistics is crucial for comprehending business problems that data analytics aims to solve, making you a more effective analyst.
Build Proficiency in Essential Business Software- (Semester 1-2)
Dedicate time to master productivity and analytical tools like Microsoft Excel for data manipulation, calculations, and basic visualization. Become comfortable with presentation software like PowerPoint for effective communication of business insights. Utilize the ''''Computer Applications in Business Lab'''' (MBA107) to its fullest, seeking additional practice and exploring practical business use cases.
Tools & Resources
Microsoft Office Suite, Online Excel tutorials (Udemy, YouTube), Practice datasets
Career Connection
These skills are non-negotiable for almost any business role, especially in data analytics where clean data and clear communication of insights are paramount.
Engage in Peer Learning and Communication Skill Development- (Semester 1-2)
Form study groups to discuss complex topics, share insights, and prepare for exams. Actively participate in the Business Communication subject (MBA106), focusing on developing presentation, report writing, and negotiation skills. Join college clubs related to business or analytics to practice public speaking and networking in a low-stakes environment.
Tools & Resources
LinkedIn Learning courses on communication, Toastmasters International (if available), College debate/presentation clubs
Career Connection
Strong communication skills are vital for articulating analytical findings to non-technical stakeholders and collaborating effectively in team projects, significantly boosting employability.
Intermediate Stage
Deep Dive into Core Business Analytics Tools and Concepts- (Semester 3-4)
While pursuing specialization electives like Data Mining, Predictive Analytics, and Business Intelligence, actively learn and apply popular analytical software. Focus on understanding the practical implementation of algorithms and techniques taught in class using relevant tools. Participate in workshops on tools like Python (for data manipulation, basic ML) or R for enhanced practical skills.
Tools & Resources
Python (Anaconda distribution, Jupyter Notebooks), R Studio, SQL, Datacamp, Kaggle for datasets, NPTEL courses on Data Science
Career Connection
Proficiency in these tools and a deep understanding of analytical concepts directly prepare you for business analyst and data science roles, making you job-ready for the Indian market.
Seek Industry Exposure through Internships and Projects- (Summer after Semester 2, and Semester 3-4)
Actively pursue and complete your Summer Internship (MBA208) with a strong focus on data analytics projects. Even if the internship is not directly analytics-focused, identify opportunities to use data for decision-making. Look for opportunities to work on live projects provided by faculty or through industry collaborations, gaining practical insights into real business challenges.
Tools & Resources
University Career Services, LinkedIn for internship search, Industry reports, Company websites
Career Connection
Practical experience in a corporate setting is invaluable, building your resume, providing networking opportunities, and helping you understand real-world business problems and their analytical solutions.
Participate in Data Analytics Competitions and Hackathons- (Semester 3-4)
Engage in online data science competitions on platforms like Kaggle, Analytics Vidhya, or take part in hackathons organized by the university or external organizations. These provide hands-on experience, allow you to build a portfolio of diverse projects, and learn from peer submissions and innovative solutions.
Tools & Resources
Kaggle, Analytics Vidhya, GitHub for showcasing projects, Medium for reading data science blogs
Career Connection
Participation demonstrates initiative, problem-solving skills, and practical application of knowledge, significantly enhancing your profile for potential employers and showcasing your abilities beyond coursework.
Advanced Stage
Master Data Visualization and Storytelling- (Semester 3-4 (Final Stage for MBA))
As you learn Data Visualization (MBA4BA02), go beyond basic charting. Focus on creating compelling, interactive dashboards and reports using tools like Tableau or Power BI. Practice presenting complex data insights clearly and concisely, translating technical findings into strategic recommendations for business leaders, a critical skill for senior analytical roles.
Tools & Resources
Tableau Public, Microsoft Power BI Desktop, Datacamp courses on data visualization, Edward Tufte''''s books
Career Connection
The ability to effectively visualize and communicate data is a critical skill for any analytics professional, enabling you to influence business decisions and stand out in competitive job interviews.
Undertake a Comprehensive Major Project (Dissertation)- (Semester 4 (Final Stage for MBA))
Your Major Project (MBA403) is a prime opportunity to apply all learned skills. Choose a challenging business analytics problem, conduct thorough research, collect and analyze relevant data, and propose innovative solutions. Collaborate closely with your faculty mentor and seek industry guidance if possible to ensure practical relevance and a high-impact outcome.
Tools & Resources
Your chosen analytical tools (Python, R, SQL, Tableau), Academic databases (JSTOR, Google Scholar), Industry reports
Career Connection
A well-executed major project serves as a capstone experience and a powerful portfolio piece, demonstrating your end-to-end analytical capabilities and readiness for complex data challenges to potential employers.
Intensive Placement Preparation and Networking- (Semester 4 (Final Stage for MBA))
Begin preparing for placements early in Semester 4. Refine your resume and LinkedIn profile, highlighting your analytical skills, projects, and internships. Practice case interviews, technical analytics questions, and behavioral questions. Network with alumni and industry professionals through university events, LinkedIn, and professional meetups to leverage connections.
Tools & Resources
University Placement Cell, LinkedIn, Mock interview platforms, Specific interview prep books for data roles
Career Connection
Proactive and targeted placement preparation, coupled with a strong professional network, significantly increases your chances of securing a desirable role in the highly competitive Indian job market for business analytics professionals.
Program Structure and Curriculum
Eligibility:
- Minimum 50% marks in Graduation. Admission based on GU-SAT/NMAT/MAT/CAT/XAT/CMAT/UPSEE entrance score followed by Group Discussion & Personal Interview.
Duration: 2 years / 4 semesters
Credits: 71 Credits
Assessment: Internal: 30%, External: 70%
Semester-wise Curriculum Table
Semester 1
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MBA101 | Management Concepts and Organizational Behavior | Core | 3 | Management Process, Planning and Organizing, Staffing and Controlling, Leadership and Motivation, Group Dynamics and Team Building, Organizational Culture and Change |
| MBA102 | Managerial Economics | Core | 3 | Demand Analysis and Forecasting, Production and Cost Analysis, Pricing Strategies, Market Structures, Profit Management, Business Cycles |
| MBA103 | Financial Accounting & Reporting | Core | 3 | Accounting Concepts and Principles, Journal, Ledger, Trial Balance, Preparation of Financial Statements, Analysis of Financial Statements, Cash Flow Statement, Introduction to IFRS |
| MBA104 | Marketing Management | Core | 3 | Marketing Environment, Consumer Behavior, Market Segmentation, Targeting, Positioning, Product Life Cycle and Strategies, Pricing Decisions, Promotion and Distribution Channels |
| MBA105 | Business Statistics | Core | 3 | Data Collection and Presentation, Measures of Central Tendency and Dispersion, Probability and Probability Distributions, Sampling and Estimation, Hypothesis Testing, Correlation and Regression Analysis |
| MBA106 | Business Communication | Core | 3 | Communication Process and Barriers, Verbal and Non-Verbal Communication, Business Writing (Emails, Reports), Presentation Skills, Negotiation and Conflict Resolution, Cross-Cultural Communication |
| MBA107 | Computer Applications in Business (Lab) | Lab | 1 | MS Word for Business Documents, MS Excel for Data Analysis and Reporting, MS PowerPoint for Presentations, Internet and Web Research, Data Management Basics, Introduction to Tally |
Semester 2
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MBA201 | Human Resource Management | Core | 3 | HR Planning, Recruitment and Selection, Training and Development, Performance Appraisal, Compensation and Benefits, Industrial Relations and Labor Laws |
| MBA202 | Financial Management | Core | 3 | Time Value of Money, Capital Budgeting Decisions, Working Capital Management, Cost of Capital and Capital Structure, Dividend Policy, Financial Markets and Institutions |
| MBA203 | Operations Management | Core | 3 | Production Planning and Control, Inventory Management, Quality Management (TQM, Six Sigma), Supply Chain Management, Layout Design and Facilities Planning, Project Management Techniques |
| MBA204 | Research Methodology | Core | 3 | Research Design and Types, Data Collection Methods (Primary & Secondary), Sampling Techniques, Data Analysis and Interpretation, Report Writing and Presentation, Ethical Issues in Research |
| MBA205 | Legal Aspects of Business | Core | 3 | Indian Contract Act, Sale of Goods Act, Companies Act, Consumer Protection Act, Intellectual Property Rights, Cyber Laws |
| MBA206 | Business Ethics & Corporate Social Responsibility | Core | 3 | Ethical Theories in Business, Corporate Governance, Models of CSR, Stakeholder Management, Environmental Ethics, Whistleblowing and Ethical Dilemmas |
| MBA207 | Marketing Research (Lab) | Lab | 1 | Introduction to SPSS/R for data analysis, Questionnaire Design and Survey Logic, Data Entry and Cleaning, Basic Statistical Analysis using software, Interpretation of Marketing Data, Report Generation using software |
| MBA208 | Summer Internship | Project/Internship | 0 | Organizational Study, Problem Identification, Project Execution, Data Collection and Analysis, Report Writing, Presentation of Findings |
Semester 3
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MBA301 | Strategic Management | Core | 3 | Strategic Planning Process, Environmental Scanning (PESTEL, SWOT), Porter''''s Five Forces Model, Strategy Formulation (Corporate, Business, Functional), Strategy Implementation, Strategic Control and Evaluation |
| MBA302 | Entrepreneurship & New Venture Creation | Core | 3 | Entrepreneurial Process, Opportunity Recognition, Business Plan Development, Sources of Funding (Venture Capital, Angel Investors), Legal and Regulatory Framework for Startups, Innovation and Creativity |
| MBA303 | Business Intelligence & Data Warehousing | Core | 3 | Introduction to Business Intelligence, Data Warehousing Concepts and Architecture, ETL Process (Extract, Transform, Load), OLAP (Online Analytical Processing), Data Mining Basics for BI, BI Tools and Reporting |
| MBA3BA01 | Data Mining for Business Decisions | Elective (Business Analytics) | 3 | Data Preprocessing and Exploration, Classification Techniques (Decision Trees, Naive Bayes), Clustering Algorithms (K-Means, Hierarchical), Association Rule Mining (Apriori), Text Mining Fundamentals, Evaluation of Data Mining Models |
| MBA3BA02 | Predictive Analytics | Elective (Business Analytics) | 3 | Linear Regression Models, Logistic Regression, Time Series Forecasting, Decision Trees and Random Forests, Model Validation and Performance Metrics, Introduction to Prescriptive Analytics |
| MBA3BA03 | Business Forecasting | Elective (Business Analytics) | 3 | Components of Time Series Data, Moving Average and Exponential Smoothing Methods, ARIMA and SARIMA Models, Causal Forecasting Techniques, Forecast Accuracy Measures, Demand Forecasting Applications |
Semester 4
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MBA401 | International Business | Core | 3 | Globalization and International Trade Theories, Foreign Exchange Markets and Risk Management, International Financial Management, International Marketing Strategies, Cross-Cultural Management, International Business Environment |
| MBA402 | Project Management | Core | 3 | Project Life Cycle, Project Planning and Scheduling (PERT/CPM), Project Risk Management, Resource Allocation and Cost Control, Project Monitoring and Evaluation, Project Closing |
| MBA4BA01 | Big Data Analytics | Elective (Business Analytics) | 3 | Introduction to Big Data and its Challenges, Hadoop Ecosystem (HDFS, MapReduce), Spark for Big Data Processing, NoSQL Databases (Cassandra, MongoDB), Data Streaming (Kafka, Storm), Cloud-based Big Data Analytics |
| MBA4BA02 | Data Visualization for Business | Elective (Business Analytics) | 3 | Principles of Data Visualization, Effective Chart Types and Graphs, Designing Dashboards and Reports, Data Storytelling, Tools like Tableau/Power BI, Interactive Visualizations |
| MBA4BA03 | Machine Learning for Business | Elective (Business Analytics) | 3 | Supervised Learning (Regression, Classification), Unsupervised Learning (Clustering, PCA), Neural Networks and Deep Learning Basics, Reinforcement Learning Introduction, Ethical Considerations in ML, Business Applications of Machine Learning |
| MBA403 | Major Project / Dissertation | Project | 6 | Problem Identification and Formulation, Literature Review, Research Design and Methodology, Data Collection and Analysis, Results and Discussion, Report Writing and Presentation |
