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MBA in Business Analytics at Shri Vishwakarma Skill University
Palwal, Haryana
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About the Specialization
What is Business Analytics at Shri Vishwakarma Skill University Palwal?
This MBA Business Analytics program at Shri Vishwakarma Skill University focuses on equipping future managers with advanced analytical skills to leverage data for strategic decision-making in the dynamic Indian business landscape. The curriculum emphasizes data science, machine learning, and statistical modeling, preparing students for roles in high-demand analytical domains across various industries. It uniquely blends managerial acumen with technical proficiency, fostering a holistic understanding of business challenges solvable through data.
Who Should Apply?
This program is ideal for fresh graduates seeking entry into the burgeoning field of data-driven management and working professionals looking to upskill in analytics for career advancement. Graduates from diverse backgrounds including engineering, commerce, science, and even arts with an aptitude for quantitative analysis, are welcome. It also suits career changers transitioning to analytical roles, providing a strong foundation in both business and data methodologies.
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 Analyst, and Operations Analyst. Entry-level salaries typically range from INR 6-10 lakhs per annum, with significant growth trajectories in leading Indian companies and multinational corporations operating in India. The curriculum also aligns with industry certifications, enhancing professional credibility and employability in the competitive job market.
Student Success Practices
Foundation Stage
Build Strong Analytical and Programming Fundamentals- (Semester 1-2)
Focus intensely on understanding core statistical concepts, data structures, and mastering foundational programming languages like R and Python, along with tools like Excel and SPSS. Regularly practice problem-solving using online platforms to solidify your technical base.
Tools & Resources
Coursera, DataCamp, Kaggle, HackerRank, GeeksforGeeks, NPTEL courses
Career Connection
A robust foundation is critical for advanced analytics and impresses recruiters looking for strong technical base for entry-level analyst roles. It enables tackling complex problems effectively.
Engage in Case Study Competitions and Group Projects- (Semester 1-2)
Actively participate in inter-college case study competitions and departmental group projects. This helps in applying theoretical knowledge to real-world business scenarios, developing teamwork, and honing presentation skills essential for analytical roles.
Tools & Resources
College library case studies, Industry reports, Online business news portals, Internal university clubs
Career Connection
Develops critical thinking, problem-solving, and collaboration skills, which are highly valued in consulting and analytical roles. Demonstrates practical application of learned concepts to business challenges.
Network with Seniors and Alumni for Mentorship- (Semester 1-2)
Connect with seniors who have completed internships or are working in analytics roles, and reach out to alumni through LinkedIn or university events. Seek their guidance on course selection, project ideas, and current industry trends and opportunities.
Tools & Resources
LinkedIn, University alumni portal, Departmental mentorship programs
Career Connection
Gaining insights into industry trends, potential internship leads, and understanding the practical challenges and rewards of an analytics career. This often opens doors to valuable opportunities.
Intermediate Stage
Undertake an Impactful Summer Internship or Mini-Projects- (Semester 3 (during summer break after Semester 2))
Secure a summer internship in a reputable company focusing on business analytics. If an internship isn''''t available, work on self-initiated mini-projects using real datasets to demonstrate practical skills in machine learning, forecasting, and data mining.
Tools & Resources
Internshala, LinkedIn Jobs, Company career portals, Kaggle datasets, UCI Machine Learning Repository
Career Connection
Hands-on experience is invaluable for placements. It allows for applying learned concepts, building a robust portfolio of practical work, and often leads to pre-placement offers from companies.
Specialize and Deepen Skills in Elective Areas- (Semester 3)
Choose electives strategically (e.g., Financial, Marketing, HR Analytics) based on your career interests. Deep dive into these areas through certifications, advanced online courses, and focused projects to build niche expertise that aligns with specific industry demands.
Tools & Resources
Specialized online courses (edX, Coursera), Industry certifications (e.g., Google Analytics, advanced Tableau/Power BI), Domain-specific books and journals
Career Connection
Niche skills make you highly attractive to companies looking for specialized analysts in specific business functions, significantly improving your employability and career trajectory in targeted fields.
Contribute to Open Source Projects or Build a Portfolio- (Semester 3)
Actively contribute to open-source data science projects or develop a personal portfolio of analytics projects on platforms like GitHub. This showcases practical coding, problem-solving, and deployment skills beyond academic assignments.
Tools & Resources
GitHub, GitLab, Personal website/blog, Medium for writing about projects
Career Connection
A strong project portfolio is a key differentiator in interviews, demonstrating initiative, practical capabilities, and real-world application of your skills, making you stand out to potential employers.
Advanced Stage
Rigorous Placement Preparation and Mock Interviews- (Semester 4)
Dedicate significant time to preparing for interviews, focusing on analytical case studies, technical questions related to statistics, ML, SQL, and general HR questions. Actively participate in mock interviews with faculty, peers, and career services.
Tools & Resources
InterviewBit, LeetCode, Glassdoor (for company-specific questions), University career services, Alumni network
Career Connection
Maximizes chances of securing top placements in desired analytical roles by refining interview skills, boosting confidence, and ensuring you are technically and professionally ready for assessment.
Work on a Capstone Dissertation or Major Project with Industry Relevance- (Semester 4)
Choose a dissertation topic that addresses a real-world business problem, ideally in collaboration with an industry partner. This provides an opportunity for in-depth research, applying comprehensive analytical skills, and delivering a tangible solution with measurable impact.
Tools & Resources
Industry mentors, Academic supervisors, Advanced analytics software, University research databases
Career Connection
A well-executed capstone project is a powerful resume booster and can demonstrate readiness for complex analytical challenges, often directly leading to full-time employment or showcasing expertise for higher roles.
Develop Soft Skills for Leadership and Communication- (Semester 4 (continuous development throughout the program))
Beyond technical skills, focus on developing effective communication, presentation, negotiation, and leadership skills. Participate in workshops, seminars, and club activities that foster these attributes, as they are crucial for career progression in management.
Tools & Resources
Toastmasters International, University communication centers, Leadership training programs, Online courses on business communication and emotional intelligence
Career Connection
While technical skills open doors, strong soft skills are essential for career progression, leading teams effectively, and communicating complex analytical insights to non-technical stakeholders, driving business impact.
Program Structure and Curriculum
Eligibility:
- Bachelor''''s Degree of minimum 3 years duration with minimum 50% (47.5% for SC/ST/PwD candidates of Haryana) aggregate marks from a recognized University or its equivalent. Preference given to candidates with Mathematics/Statistics at 10+2 or Graduation level. Must have appeared in CAT/MAT/CMAT/XAT/ATMA.
Duration: 2 years (4 semesters)
Credits: 92 Credits
Assessment: Internal: 40%, External: 60%
Semester-wise Curriculum Table
Semester 1
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MBA 101 | Management Process and Organizational Behavior | Core | 3 | Management Concepts and Functions, Planning and Decision Making, Organizing and Controlling, Foundations of Organizational Behavior, Personality, Perception and Learning, Motivation, Leadership and Group Dynamics |
| MBA 102 | Managerial Economics | Core | 3 | Basic Economic Concepts and Problem, Demand Analysis and Forecasting, Production and Cost Analysis, Market Structures and Pricing Decisions, Factor Pricing, Macroeconomic Environment |
| MBA 103 | Financial Accounting & Reporting | Core | 3 | Accounting Concepts and Principles, Journal, Ledger and Trial Balance, Preparation of Financial Statements, Depreciation Accounting and Inventory Valuation, Cash Flow Statement, Financial Statement Analysis |
| MBA 104 | Quantitative Techniques for Managers | Core | 3 | Probability and Probability Distributions, Hypothesis Testing, Correlation and Regression Analysis, Linear Programming, Transportation and Assignment Problems, Decision Theory |
| MBA 105 | Legal Aspects of Business | Core | 3 | Indian Contract Act, 1872, Sale of Goods Act, 1930, Negotiable Instruments Act, 1881, The Companies Act, 2013, Consumer Protection Act, 2019, Intellectual Property Rights |
| MBA 106 | Business Communication | Core | 3 | Process and Types of Communication, Verbal and Non-verbal Communication, Business Correspondence, Presentation Skills, Report Writing, Group Discussion and Interview Skills |
| MBA 107 | Advanced Excel for Business Analytics Lab | Lab | 2 | Data Handling and Manipulation in Excel, Advanced Functions and Formulas, Data Validation and Conditional Formatting, Pivot Tables and Charts, What-if Analysis and Solver, Introduction to VBA |
| MBA 108 | SPSS for Business Analytics Lab | Lab | 2 | Introduction to SPSS, Data Entry and Management, Descriptive Statistics, Inferential Statistics (ANOVA, t-test), Regression Analysis, Factor Analysis and Cluster Analysis |
Semester 2
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MBA 201 | Research Methodology | Core | 3 | Research Design, Sampling Techniques, Data Collection Methods, Measurement and Scaling Techniques, Hypothesis Formulation and Testing, Report Writing |
| MBA 202 | Human Resource Management | Core | 3 | HRM Concepts and Functions, Human Resource Planning, Recruitment and Selection, Training and Development, Performance Management, Compensation and Employee Relations |
| MBA 203 | Marketing Management | Core | 3 | Marketing Concepts and Environment, Consumer Behavior and Market Segmentation, Product Life Cycle and Product Strategy, Pricing Strategies, Promotion Mix, Distribution Channels and Logistics |
| MBA 204 | Financial Management | Core | 3 | Financial Goals and Time Value of Money, Capital Budgeting Decisions, Cost of Capital, Working Capital Management, Dividend Policy Decisions, Capital Structure Theories |
| MBA 205 | Operations and Supply Chain Management | Core | 3 | Operations Strategy and Productivity, Process Design and Layout, Capacity Planning and Location Decisions, Inventory Management, Quality Management, Supply Chain Management and Logistics |
| MBA 206 | Business Intelligence | Core | 3 | Introduction to Business Intelligence, Data Warehousing, OLAP and Multidimensional Analysis, Data Mining Techniques, Dashboards and Scorecards, Business Performance Management |
| MBA 207 | R & Python for Business Analytics Lab | Lab | 2 | R Programming Basics and Data Structures, Data Manipulation in R (dplyr), Python Programming Basics and Libraries (Numpy), Data Manipulation in Python (Pandas), Data Visualization in R (ggplot2), Data Visualization in Python (Matplotlib, Seaborn) |
| MBA 208 | Data Visualization using Tableau Lab | Lab | 2 | Introduction to Tableau and Connecting Data, Creating Basic Charts and Graphs, Advanced Chart Types and Dashboards, Calculated Fields and Parameters, Storytelling with Data, Tableau Server and Online Basics |
Semester 3
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MBA 301 | Business Ethics and Corporate Social Responsibility | Core | 3 | Ethical Theories and Business Ethics, Corporate Governance, Corporate Social Responsibility, Stakeholder Management, Environmental Ethics and Sustainability, Ethical Decision Making |
| MBA 302 | Business Forecasting | Core | 3 | Introduction to Forecasting, Time Series Analysis, Moving Averages and Exponential Smoothing, Regression Based Forecasting, ARIMA Models, Forecast Accuracy and Evaluation |
| MBA 303 | Machine Learning for Business | Core | 3 | Introduction to Machine Learning, Supervised Learning (Regression, Classification), Unsupervised Learning (Clustering, Association Rules), Decision Trees and Random Forests, Model Evaluation and Validation, Applications of Machine Learning in Business |
| MBA 304 | Prescriptive Analytics | Core | 3 | Introduction to Optimization, Linear Programming, Integer Programming, Network Models, Simulation, Decision Analysis and Decision Trees |
| MBA 305 | Project Management | Core | 3 | Project Life Cycle and Project Selection, Project Planning and Scheduling (PERT/CPM), Resource Allocation and Cost Management, Project Risk Management, Project Monitoring and Control, Project Closure and Agile Project Management |
| MBA 306 | Open Elective | Elective | 3 | |
| MBA 307 | Business Analytics Project Lab | Lab | 2 | Problem Definition and Data Collection, Data Preprocessing and Feature Engineering, Model Building and Validation, Data Visualization and Reporting, Case Study Analysis, Project Documentation and Presentation |
| MBA 308 | Summer Internship / Project Report | Project | 4 | Problem Identification and Scope, Data Collection and Methodology, Analysis and Interpretation of Results, Findings and Recommendations, Report Writing and Presentation, Industry Application |
Semester 4
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MBA 401 | Strategic Management | Core | 3 | Strategic Management Process, Environmental Analysis and Industry Structure, SWOT Analysis, Corporate Level Strategies, Business Level Strategies, Strategy Implementation and Control |
| MBA 402 | Data Mining & Warehousing | Core | 3 | Introduction to Data Mining, Data Preprocessing and Data Cleaning, Data Warehousing Architecture and Design, OLAP Operations, Association Rule Mining, Classification and Prediction, Clustering |
| MBA 403 | Artificial Intelligence for Business | Core | 3 | Introduction to Artificial Intelligence, Machine Learning Overview, Deep Learning Fundamentals, Natural Language Processing for Business, Computer Vision Basics, AI Ethics and Business Applications |
| MBA BA 01 | Financial Analytics (Specialization Elective) | Elective (Choice) | 3 | Financial Modeling, Portfolio Analytics, Risk Analytics and Management, Fintech Analytics, Algorithmic Trading Strategies, Fraud Detection in Finance |
| MBA BA 02 | Marketing Analytics (Specialization Elective) | Elective (Choice) | 3 | Customer Analytics and Segmentation, Web Analytics and Digital Marketing, Social Media Analytics, Campaign Optimization and ROI, Marketing Mix Modeling, Customer Lifetime Value (CLV) |
| MBA BA 03 | HR Analytics (Specialization Elective) | Elective (Choice) | 3 | Workforce Planning and Analytics, Recruitment and Onboarding Analytics, Performance Analytics, Retention and Attrition Analytics, Compensation and Benefits Analytics, HR Dashboards and Reporting |
| MBA BA 04 | Operations Analytics (Specialization Elective) | Elective (Choice) | 3 | Supply Chain Analytics and Optimization, Inventory Optimization, Logistics and Transportation Analytics, Quality Control and Analytics, Demand Forecasting and Planning, Production Scheduling and Optimization |
| MBA BA 05 | Retail Analytics (Specialization Elective) | Elective (Choice) | 3 | Store Performance Analytics, Merchandising and Assortment Analytics, Pricing Optimization, Customer Segmentation in Retail, Loyalty Program Analytics, E-commerce Analytics |
| MBA BA 06 | Healthcare Analytics (Specialization Elective) | Elective (Choice) | 3 | Clinical Data Analytics, Public Health Analytics, Patient Flow Optimization, Healthcare Fraud Detection, Pharmaceutical Analytics, Health Economics Analytics |
| MBA 407 | Dissertation / Project Report | Project | 6 | Advanced Research Methodology, Complex Data Analysis and Model Implementation, Problem Solving and Solution Development, Project Management and Execution, Thesis Writing and Presentation, Viva Voce |
