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MBA in Business Analytics at RK University
Rajkot, Gujarat
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About the Specialization
What is Business Analytics at RK University Rajkot?
This Business Analytics program at RK University focuses on equipping future managers with the skills to leverage data for strategic decision-making. With India''''s rapid digital transformation, there''''s immense demand for professionals who can analyze complex datasets to uncover insights. This program differentiates itself by combining core management principles with advanced analytical techniques, preparing graduates for a data-driven business landscape.
Who Should Apply?
This program is ideal for fresh graduates from any discipline seeking entry into high-growth analytical roles in various sectors. It also caters to working professionals aiming to upskill in data science, and career changers transitioning into the dynamic field of business intelligence. A keen interest in numbers, problem-solving, and technology, alongside a bachelor''''s degree, forms the core prerequisite for this specialization.
Why Choose This Course?
Graduates of this program can expect to pursue India-specific career paths such as Business Analyst, Data Analyst, Market Research Analyst, and Management Consultant. Entry-level salaries can range from INR 4-7 lakhs, with experienced professionals potentially earning INR 10-20 lakhs or more. Growth trajectories are steep, with opportunities to lead analytics teams in Indian and global companies, aligning with certifications like those from IBM or SAS.
Student Success Practices
Foundation Stage
Master Core Management Fundamentals- (Semester 1-2)
Dedicate time to thoroughly understand foundational management concepts (Marketing, Finance, HR) as they provide the business context for analytics. Form study groups with peers to discuss case studies and clarify complex theories, building a strong base for interdisciplinary learning.
Tools & Resources
Harvard Business Review articles, NPTEL management courses, Peer study groups
Career Connection
A strong grasp of management fundamentals makes analytics outputs more relevant and actionable for business stakeholders, enhancing strategic impact and career growth in management roles.
Develop Strong Quantitative Skills- (Semester 1-2)
Focus on excelling in Business Statistics and Managerial Economics. Utilize online platforms for additional practice in quantitative aptitude and logical reasoning, which are crucial for analytical roles. Engage with real-world data problems provided by professors to sharpen analytical thinking.
Tools & Resources
Khan Academy for statistics, Excel for data manipulation, Practice problem sets
Career Connection
Robust quantitative skills are non-negotiable for business analytics roles, directly impacting performance in data interpretation, model building, and problem-solving, which are key for placements.
Enhance Communication and Presentation Skills- (Semester 1-2)
Actively participate in business communication classes, debate clubs, and group presentations. Practice explaining complex ideas simply and concisely. This is vital for presenting analytical insights to non-technical business leaders.
Tools & Resources
Toastmasters International chapters, Presentation software (PowerPoint, Google Slides), Feedback from peers and faculty
Career Connection
Effective communication is critical for translating data insights into strategic business recommendations, making graduates valuable assets in companies and improving their chances in interviews.
Intermediate Stage
Gain Proficiency in Analytical Tools- (Semester 3)
Beyond classroom learning, invest time in mastering essential analytical tools like Python (with libraries like Pandas, NumPy, Scikit-learn) and R, as well as visualization tools like Tableau or Power BI. Complete online certifications to demonstrate practical expertise.
Tools & Resources
Coursera/Udemy courses (Python, R, Tableau), Kaggle for practice datasets, Official documentation for tools
Career Connection
Hands-on proficiency with industry-standard tools is a primary requirement for Business Analytics roles, directly making candidates more employable and effective from day one.
Undertake Live Industry Projects and Internships- (Semester 3)
Actively seek and participate in live projects offered by the university or through internships. This provides real-world exposure to business problems and the application of analytical techniques, building a strong portfolio. Network with industry professionals during these experiences.
Tools & Resources
University career services, LinkedIn for industry contacts, Networking events
Career Connection
Practical experience through projects and internships significantly enhances a student''''s resume, often leading to pre-placement offers and providing invaluable insights into industry demands and work culture.
Deepen Specialization in Predictive Modeling- (Semester 3)
Focus on understanding advanced predictive analytics techniques. Participate in data science competitions (e.g., on Kaggle) to apply theoretical knowledge and develop problem-solving skills with diverse datasets. Collaborate with peers on complex projects.
Tools & Resources
Kaggle competitions, Advanced statistics textbooks, Online forums for data science
Career Connection
Specialized knowledge in predictive modeling is highly sought after, positioning students for advanced analytical roles that involve forecasting, risk assessment, and strategic planning, commanding better salary packages.
Advanced Stage
Focus on Big Data and Machine Learning Applications- (Semester 4)
Dive deep into Big Data technologies like Hadoop/Spark and Machine Learning algorithms. Explore their applications in various business contexts. Work on a capstone project that integrates these advanced concepts, simulating a real-world analytics challenge.
Tools & Resources
Cloud platforms (AWS, Azure, GCP for Big Data), TensorFlow/PyTorch for ML, GitHub for project showcase
Career Connection
Expertise in Big Data and Machine Learning is crucial for high-end analytics and data scientist roles, opening doors to cutting-edge opportunities in large enterprises and tech firms in India.
Prepare for Placements and Mock Interviews- (Semester 4)
Engage rigorously in placement preparation activities, including resume building, mock interviews (technical and HR), and group discussions. Practice explaining your projects and analytical methodologies clearly and confidently. Seek feedback from career services and alumni.
Tools & Resources
Career services workshops, Mock interview platforms, Alumni network for guidance
Career Connection
Thorough preparation ensures confidence and competence during the placement process, significantly increasing the likelihood of securing desirable job offers from top companies.
Network Strategically and Build a Professional Brand- (Semester 4)
Actively participate in industry seminars, webinars, and conferences. Connect with professionals on LinkedIn, showcase your projects and skills, and contribute to relevant discussions. This helps in building a professional network and personal brand in the analytics community.
Tools & Resources
LinkedIn profiles, Industry conferences (e.g., Analytics India Summit), Professional blogs/articles
Career Connection
A strong professional network can lead to mentorship, job referrals, and insights into industry trends, accelerating career progression and opening doors to unforeseen opportunities post-graduation.
Program Structure and Curriculum
Eligibility:
- Bachelor’s Degree of minimum 3 years duration with at least 50% (45% in case of candidate belonging to reserved category) marks in the qualifying examination.
Duration: 2 years (4 semesters)
Credits: 74 Credits
Assessment: Internal: 30%, External: 70%
Semester-wise Curriculum Table
Semester 1
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 1010101 | Principles of Management | Core | 3 | Introduction to Management, Planning, Organizing, Staffing and Directing, Controlling, Managerial Ethics |
| 1010102 | Managerial Economics | Core | 3 | Introduction to Managerial Economics, Demand Analysis, Supply Analysis, Production and Cost Analysis, Market Structures, Pricing Strategies |
| 1010103 | Accounting for Managers | Core | 3 | Introduction to Accounting, Financial Accounting Concepts, Financial Statement Analysis, Cost Accounting, Budgeting and Variance Analysis, Decision Making |
| 1010104 | Organizational Behavior | Core | 3 | Introduction to OB, Individual Behavior, Group Dynamics and Teamwork, Motivation and Leadership, Organizational Culture, Conflict and Stress Management |
| 1010105 | Business Statistics | Core | 3 | Introduction to Statistics, Probability and Probability Distributions, Sampling and Estimation, Hypothesis Testing, Correlation and Regression, Time Series Analysis |
| 1010106 | Business Communication | Core | 3 | Fundamentals of Communication, Verbal and Non-verbal Communication, Written Communication, Oral Communication, Presentations and Reports, Cross-cultural Communication |
| 1010107 | Legal Aspects of Business | Core | 3 | Indian Contract Act, Sale of Goods Act, Negotiable Instruments Act, Companies Act, Consumer Protection Act, Intellectual Property Rights |
| 1010108 | Management Information System | Core | 3 | Introduction to MIS, Information Systems for Business, Databases and Data Warehousing, Decision Support Systems, Enterprise Systems, IT Security and Ethics |
Semester 2
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 1010201 | Financial Management | Core | 3 | Introduction to Financial Management, Capital Budgeting, Working Capital Management, Cost of Capital, Capital Structure, Dividend Policy |
| 1010202 | Marketing Management | Core | 3 | Introduction to Marketing, Market Segmentation and Targeting, Product Management, Pricing Strategies, Promotion and Advertising, Distribution Channels |
| 1010203 | Human Resource Management | Core | 3 | Introduction to HRM, Human Resource Planning, Recruitment and Selection, Training and Development, Performance Management, Compensation and Benefits |
| 1010204 | Operations Management | Core | 3 | Introduction to Operations Management, Product and Process Design, Location and Layout Planning, Production Planning and Control, Quality Management, Supply Chain Management |
| 1010205 | Research Methodology | Core | 3 | Introduction to Research, Research Design, Data Collection Methods, Sampling Design, Data Analysis, Report Writing |
| 1010206 | Entrepreneurship & Startups | Core | 3 | Concept of Entrepreneurship, Business Idea Generation, Business Plan Development, Funding for Startups, Legal and Regulatory Aspects, Marketing for Startups |
| 1010207 | Business Environment & Ethics | Core | 3 | Economic Environment, Political and Legal Environment, Socio-Cultural Environment, Technological Environment, Ethical Theories in Business, Corporate Social Responsibility |
| 1010208 | Digital Business Management | Core | 3 | Introduction to Digital Business, E-commerce Models, Digital Marketing Strategies, Social Media Management, Cyber Security in Business, Digital Transformation |
Semester 3
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 10103BA1 | Foundations of Business Analytics | Elective | 3 | Introduction to Business Analytics, Data Types and Sources, Descriptive Analytics, Data Cleaning and Preparation, Basic Statistical Tools, Spreadsheet Modeling |
| 10103BA2 | Predictive Analytics | Elective | 3 | Introduction to Predictive Modeling, Regression Analysis, Classification Techniques, Time Series Forecasting, Decision Trees, Model Evaluation |
| 10103BA3 | Data Visualization and Storytelling | Elective | 3 | Principles of Data Visualization, Tools for Visualization (Tableau/Power BI), Types of Charts and Graphs, Dashboard Design, Telling Stories with Data, Interactive Visualizations |
| 10103P1 | Project Work Phase – I | Project | 4 | Problem Identification, Literature Review, Research Design, Data Collection Planning, Preliminary Analysis, Report Writing |
Semester 4
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 10104BA1 | Big Data Analytics | Elective | 3 | Introduction to Big Data, Hadoop Ecosystem, Spark Framework, NoSQL Databases, Big Data Technologies, Big Data Applications |
| 10104BA2 | Machine Learning for Business | Elective | 3 | Introduction to Machine Learning, Supervised Learning, Unsupervised Learning, Deep Learning Basics, Reinforcement Learning, ML Applications in Business |
| 10104BA3 | Business Intelligence and Data Warehousing | Elective | 3 | Introduction to Business Intelligence, Data Warehousing Concepts, OLAP and Data Mining, ETL Process, BI Tools and Applications, Data Governance |
| 10104P2 | Project Work Phase – II | Project | 4 | Data Analysis and Interpretation, Statistical Software Application, Findings and Recommendations, Report Finalization, Presentation of Project, Implementation Strategy |
