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MBA in Business Analytics at Rayat Institute of Engineering & Technology
Shahid Bhagat Singh Nagar, Punjab
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About the Specialization
What is Business Analytics at Rayat Institute of Engineering & Technology Shahid Bhagat Singh Nagar?
This Business Analytics program at Rayat Institute of Engineering & Technology, affiliated with IKGPTU, focuses on equipping students with advanced analytical skills to drive data-driven decision-making. In the rapidly evolving Indian industry, the ability to extract insights from vast datasets is crucial, and this program trains future managers to leverage tools and techniques for business growth. It emphasizes both theoretical foundations and practical applications of analytics to address real-world business problems.
Who Should Apply?
This program is ideal for fresh graduates from any discipline seeking entry into high-growth data-driven roles, as well as working professionals looking to upskill in analytics for career advancement. Individuals with a strong aptitude for numbers, problem-solving, and technology, who aspire to become data strategists, business intelligence managers, or analytics consultants in India''''s dynamic market, 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 Risk Analyst, or Operations Analyst in diverse sectors. Entry-level salaries typically range from INR 4-7 LPA, with experienced professionals earning INR 10-25+ LPA, depending on skill and company. The program also aligns with foundational knowledge required for certifications like Microsoft Certified: Azure Data Scientist Associate or Google''''s Professional Data Engineer.
Student Success Practices
Foundation Stage
Build a Strong Analytical Foundation- (Semester 1-2)
Focus on excelling in core quantitative subjects like Business Statistics and Quantitative Techniques. Regularly practice problem-solving to strengthen your logical and analytical thinking, which are critical for advanced analytics. Join peer study groups to clarify concepts and work through challenging assignments collaboratively.
Tools & Resources
Khan Academy, Coursera for basic stats, Excel for data manipulation, Peer study circles
Career Connection
Mastering these fundamentals ensures a solid base for understanding complex analytics models, crucial for future roles in data analysis and business intelligence.
Cultivate Basic Programming Skills- (Semester 1-2)
While formal programming starts later, get an early start on foundational coding concepts. Explore free online resources to understand the basics of Python or R, focusing on data types, variables, and control structures. This proactive step will ease into the dedicated programming courses in later semesters.
Tools & Resources
Codecademy (Python/R), HackerRank for practice, GeeksforGeeks for tutorials
Career Connection
Early exposure to programming languages like Python or R provides a significant advantage, making it easier to grasp advanced analytics tools and techniques required by employers.
Engage with Business Case Studies- (Semester 1-2)
Actively participate in discussions on business case studies from various domains (marketing, finance, operations). Analyze how businesses make decisions and identify areas where data can provide insights. This helps connect theoretical knowledge with practical business problems.
Tools & Resources
Harvard Business Review cases, IIM-style case studies, Live discussions in class
Career Connection
Developing a business-first mindset early helps in framing analytical problems effectively and communicating insights to non-technical stakeholders, a key skill for a Business Analyst.
Intermediate Stage
Deep Dive into Data Tools & Techniques- (Semester 3-4)
Beyond classroom learning in Data Warehousing & Data Mining, and R/Python Programming, spend extra time practicing with real datasets. Participate in hackathons or data challenges to apply your skills in a competitive environment and build a portfolio of projects.
Tools & Resources
Kaggle competitions, GitHub for project showcase, Jupyter Notebook, RStudio
Career Connection
Hands-on experience with industry-standard tools and techniques makes you job-ready, demonstrating practical expertise to potential employers for internship and placement roles.
Seek Industry Internships and Live Projects- (Semester 3-4)
Actively look for internships or live projects, even if unpaid, with startups or SMEs in the Punjab region or major Indian cities. This practical exposure helps you understand real-world business problems, data complexities, and gain valuable industry experience. Network with alumni and faculty for leads.
Tools & Resources
Internshala, LinkedIn, College placement cell
Career Connection
Internships are crucial for gaining practical exposure, building a professional network, and often lead to pre-placement offers, significantly boosting career entry prospects.
Develop Specialization-Specific Communication Skills- (Semester 3-4)
Focus on articulating analytical insights clearly to both technical and non-technical audiences. Practice presenting your findings from projects, emphasizing the business implications. Participate in debates or presentations to hone your communication and storytelling abilities.
Tools & Resources
Toastmasters International (if available), Presentation software (PowerPoint, Google Slides), Storytelling with Data (book/resources)
Career Connection
The ability to translate complex data into actionable business recommendations is highly valued, differentiating you in interviews and future leadership roles.
Advanced Stage
Master Advanced Analytics & Machine Learning Applications- (Semester 4)
Dedicate time to mastering advanced topics in Big Data Analytics and Machine Learning. Work on capstone projects that integrate multiple analytical techniques to solve complex business challenges. Consider taking specialized online courses in areas like Deep Learning or Natural Language Processing.
Tools & Resources
Google Cloud/AWS free tier, Databricks Community Edition, TensorFlow/PyTorch tutorials, Udemy/Coursera advanced courses
Career Connection
Proficiency in advanced analytics and machine learning tools is essential for roles like Data Scientist and Machine Learning Engineer, positions that command higher salaries in the Indian market.
Prepare for Placements with mock interviews- (Semester 4)
Regularly participate in mock interviews and group discussions organized by the college''''s placement cell. Focus on behavioral questions, technical analytics questions, and case-based problem-solving. Refine your resume and LinkedIn profile to highlight analytical projects and skills effectively.
Tools & Resources
Mock interview platforms, Aptitude test preparation books, LinkedIn profile optimization guides, College placement services
Career Connection
Thorough placement preparation significantly increases your chances of securing desired roles with top companies, converting academic knowledge into a successful career launch.
Build a Professional Network and Personal Brand- (Semester 4)
Actively network with industry professionals, alumni, and faculty. Attend industry seminars, conferences, and workshops (online or offline) relevant to business analytics. Create an online presence by writing blogs, contributing to open-source projects, or sharing insights on platforms like LinkedIn.
Tools & Resources
LinkedIn Professional Network, Industry conferences (e.g., Data Science Summit India), Medium for blogging, Open-source communities
Career Connection
A strong professional network opens doors to job opportunities, mentorship, and continuous learning, while a personal brand enhances your visibility and credibility in the analytics industry.
Program Structure and Curriculum
Eligibility:
- Bachelor''''s degree in any discipline with a minimum of 50% marks (45% for SC/ST category) from a recognized university.
Duration: 2 years / 4 semesters
Credits: 104 Credits
Assessment: Internal: 40% (for theory papers), External: 60% (for theory papers)
Semester-wise Curriculum Table
Semester 1
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MBA101-20 | Management Process & Organizational Behavior | Core | 4 | Management process and functions, Organizational behavior theories, Motivation and leadership, Group dynamics and team building, Conflict and stress management |
| MBA103-20 | Managerial Economics | Core | 4 | Demand and supply analysis, Production and cost theory, Market structures and pricing strategies, National income accounting, Business cycles and forecasting |
| MBA105-20 | Accounting for Management | Core | 4 | Financial accounting principles, Financial statements analysis, Cost accounting concepts, Budgeting and budgetary control, Capital budgeting decisions |
| MBA107-20 | Business Statistics | Core | 4 | Data collection and presentation, Measures of central tendency and dispersion, Probability and probability distributions, Sampling and estimation, Hypothesis testing |
| MBA109-20 | Marketing Management | Core | 4 | Marketing concepts and philosophies, Market segmentation and targeting, Product life cycle and new product development, Pricing strategies, Promotion and distribution channels |
| MBA111-20 | Business Environment | Core | 4 | Economic environment, Political and legal environment, Socio-cultural and technological environment, Global business environment, Business ethics and corporate social responsibility |
Semester 2
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MBA201-20 | Human Resource Management | Core | 4 | HR planning and recruitment, Selection and placement, Training and development, Performance appraisal and compensation, Industrial relations and employee welfare |
| MBA203-20 | Financial Management | Core | 4 | Financial goals and objectives, Capital structure decisions, Working capital management, Dividend policy, Capital budgeting techniques |
| MBA205-20 | Operations Management | Core | 4 | Production planning and control, Inventory management, Quality management and control, Supply chain management, Project management |
| MBA207-20 | Research Methodology | Core | 4 | Research design and formulation, Data collection methods, Sampling techniques, Scaling techniques, Data analysis and report writing |
| MBA209-20 | Quantitative Techniques for Management | Core | 4 | Linear programming, Transportation and assignment problems, Game theory and decision theory, Queuing theory, Simulation |
| MBA211-20 | Business Law | Core | 4 | Indian Contract Act, Sale of Goods Act, Negotiable Instruments Act, Consumer Protection Act, Companies Act, Cyber Law |
Semester 3
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MBA301-20 | Strategic Management | Core | 4 | Strategic analysis and formulation, Strategy implementation and control, Competitive advantage, Corporate governance, Mergers and acquisitions |
| MBA303-20 | Enterprise Resource Planning (ERP) | Core | 4 | ERP concepts and architecture, ERP modules and implementation, Business Process Reengineering, Supply Chain Integration, CRM and E-commerce with ERP |
| MBA305-20 | International Business Management | Core | 4 | Globalization and international trade theories, Foreign exchange markets, International finance and investment, Global marketing strategies, Cultural environment in international business |
| MBA-BA-301-20 | Data Warehousing & Data Mining | Specialization Elective (Business Analytics) | 4 | Data warehousing concepts, ETL process and OLAP, Data mining techniques, Association rules and market basket analysis, Classification and clustering |
| MBA-BA-302-20 | R-Programming | Specialization Elective (Business Analytics) | 4 | R environment and data structures, Control flow and functions in R, Data manipulation with dplyr and tidyr, Statistical analysis using R, Data visualization with ggplot2 |
| MBA-PR-301-20 | Project Report | Project | 8 | Problem identification and definition, Literature review, Research methodology and design, Data collection and analysis, Findings, conclusions, and recommendations |
Semester 4
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MBA401-20 | Entrepreneurship Development | Core | 4 | Entrepreneurial process and characteristics, New venture creation, Business plan preparation, Funding opportunities for startups, Innovation and small business management |
| MBA403-20 | Total Quality Management | Core | 4 | Quality philosophies and principles, TQM implementation strategies, Quality tools and techniques, Process improvement methodologies, ISO standards and Six Sigma |
| MBA-BA-401-20 | Business Analytics Applications | Specialization Elective (Business Analytics) | 4 | Marketing analytics, Financial analytics, HR analytics and talent management, Operations and supply chain analytics, Web and social media analytics |
| MBA-BA-402-20 | Big Data Analytics | Specialization Elective (Business Analytics) | 4 | Big data concepts and characteristics, Hadoop ecosystem and MapReduce, Spark for large-scale data processing, NoSQL databases, Real-time data streaming |
| MBA-BA-403-20 | Python Programming for Analytics | Specialization Elective (Business Analytics) | 4 | Python fundamentals and data types, Numpy for numerical computing, Pandas for data manipulation and analysis, Matplotlib and Seaborn for data visualization, Introduction to Scikit-learn |
| MBA-BA-404-20 | Machine Learning for Business | Specialization Elective (Business Analytics) | 4 | Supervised and unsupervised learning, Regression and classification algorithms, Clustering techniques, Model evaluation and selection, Introduction to deep learning |
| MBA-VV-401-20 | Comprehensive Viva Voce | Viva Voce | 4 | Overall MBA curriculum understanding, Specialization knowledge in Business Analytics, Current business trends and challenges, Analytical and problem-solving skills, Communication and presentation abilities |
