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MBA in Business Analytics at PES Institute of Advanced Management Studies
Shivamogga, Karnataka
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About the Specialization
What is Business Analytics at PES Institute of Advanced Management Studies Shivamogga?
This Business Analytics program at P.E.S. Institute of Advanced Management Studies focuses on equipping students with advanced analytical skills to transform raw data into actionable business insights. Amidst India''''s rapidly digitizing economy, this specialization is crucial for professionals seeking to leverage data for strategic decision-making across various sectors. The program emphasizes both theoretical foundations and practical application of analytics tools.
Who Should Apply?
This program is ideal for fresh graduates with a quantitative aptitude seeking entry into the booming data analytics field in India. It also caters to working professionals aiming to upskill and transition into data-driven roles. Individuals from diverse academic backgrounds, including engineering, commerce, and science, who possess strong analytical thinking and problem-solving skills, are well-suited for this specialization.
Why Choose This Course?
Graduates of this program can expect diverse India-specific career paths such as Data Analyst, Business Intelligence Analyst, Data Scientist, and Analytics Consultant in top Indian and multinational companies. Entry-level salaries typically range from INR 4-7 LPA, growing significantly with experience. The program aligns with industry certifications like Tableau Specialist or Microsoft Certified: Azure Data Scientist Associate, enhancing professional growth.
Student Success Practices
Foundation Stage
Master Core Business Fundamentals & Quantitative Skills- (Semester 1-2)
Dedicate time to thoroughly understand foundational MBA subjects like Accounting, Marketing, Finance, and especially Quantitative Techniques. Simultaneously, build strong statistical and analytical reasoning skills crucial for business analytics. Form study groups to discuss complex topics and solve case studies.
Tools & Resources
Textbooks, Online courses (Coursera, edX for statistics/Excel), Peer study groups
Career Connection
A solid understanding of business domains combined with quantitative skills forms the bedrock for effective data interpretation and problem-solving in any analytics role, making you a more valuable asset to potential employers.
Build a Strong Foundation in Business Analytics Concepts- (Semester 2)
Focus intently on the core ''''Business Analytics'''' subject in Semester 2, understanding data types, descriptive statistics, and basic predictive modeling. Practice using spreadsheet software (like MS Excel) for data manipulation and visualization, which is a fundamental tool across all analytics roles.
Tools & Resources
MS Excel, R/Python basics (self-study), Kaggle introductory datasets
Career Connection
Developing early proficiency in core analytics concepts and tools prepares you for more advanced topics and ensures you''''re ready for initial analytical tasks during internships or entry-level positions.
Engage in Early Networking and Industry Exploration- (Semester 1-2)
Attend webinars, workshops, and guest lectures on business analytics. Connect with alumni or industry professionals on LinkedIn to understand current trends and career paths within the Indian analytics landscape. Start exploring different sub-fields of business analytics.
Tools & Resources
LinkedIn, Industry conferences (virtual/local), College alumni network events
Career Connection
Early networking helps in identifying potential internship opportunities, understanding industry expectations, and refining your career aspirations, giving you a competitive edge in the job market.
Intermediate Stage
Deep Dive into Specialization Electives and Tools- (Semester 3)
Choose your Business Analytics electives wisely in Semester 3. Dedicate significant effort to mastering specific tools and techniques like Data Warehousing, Data Mining, Big Data technologies (Hadoop, Spark), and Machine Learning algorithms. Implement projects using these tools.
Tools & Resources
SQL, Python (Pandas, NumPy, Scikit-learn), R, Tableau/Power BI, Cloud platforms (AWS/Azure basic services)
Career Connection
Hands-on experience with industry-relevant tools and advanced analytics techniques makes you highly desirable for specialized roles like Data Scientist or BI Developer in Indian companies.
Undertake an Industry-Relevant Internship- (Between Semester 2 and 3, or during Semester 3 break)
Actively seek and complete an internship in a Business Analytics role after Semester 2 or during Semester 3. Focus on applying theoretical knowledge to real-world business problems, contributing meaningfully to projects, and building a strong professional network within the host company.
Tools & Resources
College placement cell, Internship portals (Internshala, LinkedIn), Company career pages
Career Connection
Internships are critical for gaining practical experience, building a professional portfolio, and often lead to pre-placement offers (PPOs) or strong recommendations for future job applications in India.
Participate in Data Science Competitions & Projects- (Semester 3)
Engage in data science competitions on platforms like Kaggle or Analytics Vidhya. Work on independent or group projects using real datasets to solve business problems. This builds a robust portfolio and hones problem-solving and collaboration skills.
Tools & Resources
Kaggle, Analytics Vidhya, GitHub for project showcasing, Industry case studies
Career Connection
A strong project portfolio demonstrates practical skills to recruiters and significantly boosts your chances of securing roles in highly competitive Indian analytics firms. Winning competitions adds significant value.
Advanced Stage
Execute a Comprehensive Business Analytics Project- (Semester 4)
Your Semester 4 project work is a capstone experience. Choose a complex business problem, apply advanced analytics techniques (AI, IoT, Cloud Analytics), collect real or simulated data, perform thorough analysis, and present actionable insights. Focus on end-to-end implementation.
Tools & Resources
Advanced ML frameworks (TensorFlow, PyTorch), Cloud platforms (AWS Sagemaker, Azure ML Studio), Domain-specific datasets
Career Connection
A well-executed project demonstrates your ability to independently tackle significant business challenges using advanced analytics, making you ready for lead analyst or consultant roles.
Focus on Placement Preparation and Soft Skills- (Semester 4)
Intensively prepare for placements by practicing aptitude tests, group discussions, and technical interviews. Refine your communication, presentation, and negotiation skills. Understand industry-specific interview patterns for analytics roles in India. Tailor your resume and LinkedIn profile.
Tools & Resources
Mock interviews, Aptitude test platforms, Resume builders, LinkedIn optimization guides
Career Connection
Strong communication and interview skills are crucial for converting opportunities into job offers, especially in companies looking for well-rounded business analysts and data scientists.
Continuous Learning and Specialization in Emerging Tech- (Ongoing, particularly Semester 4 and beyond)
Stay updated with the latest trends in AI, Machine Learning, Cloud Analytics, and Data Governance. Consider pursuing advanced certifications in specific tools or domains. Develop a mindset of lifelong learning to adapt to the rapidly evolving analytics landscape in India.
Tools & Resources
Online certifications (IBM, Google, Microsoft), Industry blogs and research papers, Professional associations
Career Connection
Continuous learning ensures long-term career growth, enabling you to take on leadership roles and remain competitive in the fast-paced Indian tech and analytics industry.
Program Structure and Curriculum
Eligibility:
- Any graduate with 50% aggregate marks (45% for SC/ST/CAT-I/OBC), Must have appeared for PGCET/CMAT/K-MAT/MAT.
Duration: 2 Years (4 Semesters)
Credits: 116 Credits
Assessment: Internal: 50%, External: 50%
Semester-wise Curriculum Table
Semester 1
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MBA C.1.1 | Business Ethics and Corporate Governance | Core | 4 | Ethics in Business, Corporate Governance Models, Corporate Social Responsibility, Business & Environment, Legal & Regulatory Framework |
| MBA C.1.2 | Indian Economic Environment | Core | 4 | Macroeconomic Concepts, Overview of Indian Economy, Economic Reforms in India, Sectoral Performance, Government Policies & Business |
| MBA C.1.3 | Organisational Behaviour and Human Resources Management | Core | 4 | Foundations of Organisational Behaviour, Personality and Perception, Motivation and Leadership, Group Dynamics and Team Building, Human Resources Functions, Performance Management Systems |
| MBA C.1.4 | Accounting for Managers | Core | 4 | Financial Accounting Principles, Preparation of Financial Statements, Cost Accounting Concepts, Budgeting and Variance Analysis, Management Control Systems |
| MBA C.1.5 | Marketing Management | Core | 4 | Core Marketing Concepts, Marketing Environment Analysis, Consumer Behavior & Market Segmentation, Product and Pricing Strategies, Promotion and Distribution Channels |
| MBA C.1.6 | Quantitative Techniques for Business Decisions | Core | 4 | Introduction to Quantitative Techniques, Probability and Probability Distributions, Statistical Inference and Hypothesis Testing, Correlation and Regression Analysis, Linear Programming and Decision Theory |
Semester 2
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MBA C.2.1 | Management Information System | Core | 4 | Role of Information Systems, Database Management Systems, Decision Support Systems, Enterprise Systems (ERP), E-commerce and M-commerce, IT Security and Ethics |
| MBA C.2.2 | Research Methods for Business | Core | 4 | Business Research Process, Research Design Types, Data Collection Methods, Sampling Techniques, Data Analysis and Interpretation, Report Writing and Presentation |
| MBA C.2.3 | Financial Management | Core | 4 | Financial Goals and Objectives, Capital Budgeting Decisions, Cost of Capital and Capital Structure, Working Capital Management, Dividend Policy and Valuation |
| MBA C.2.4 | Production and Operations Management | Core | 4 | Operations Strategy and Competitiveness, Facility Location and Layout, Production Planning and Control, Inventory Management Techniques, Quality Management and TQM, Project Management |
| MBA C.2.5 | Business Analytics | Core | 4 | Introduction to Business Analytics, Data Collection and Preparation, Descriptive Analytics Techniques, Predictive Analytics Models, Prescriptive Analytics and Optimization, Data Visualization Fundamentals |
| MBA C.2.6 | Entrepreneurship and Small Business Management | Core | 4 | Concept of Entrepreneurship, Idea Generation and Opportunity Analysis, Business Plan Development, Sources of Finance for Startups, Managing Small Businesses, Government Support for Entrepreneurs |
Semester 3
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MBA C.3.1 | International Business | Core | 4 | Globalization and International Trade Theories, Cultural Environment of International Business, International Trade Policies and Agreements, Foreign Exchange Markets, Global Marketing Strategies |
| MBA C.3.2 | Strategic Management | Core | 4 | Strategic Management Process, Environmental Analysis, Strategy Formulation, Strategy Implementation, Strategic Control and Evaluation |
| MBA C.3.3 | Legal Aspects of Business | Core | 4 | Indian Contract Act 1872, Sale of Goods Act 1930, Consumer Protection Act 2019, Companies Act 2013, Cyber Law and E-commerce, Intellectual Property Rights |
| MBA BA E.3.1 | Data Warehousing and Data Mining | Elective (Business Analytics) | 4 | Data Warehousing Concepts, Data Marts and OLAP, ETL Process, Data Mining Techniques, Association Rule Mining, Classification and Clustering |
| MBA BA E.3.2 | Big Data Analytics | Elective (Business Analytics) | 4 | Introduction to Big Data, Hadoop Ecosystem, MapReduce Framework, HDFS and Spark, NoSQL Databases, Big Data Tools and Technologies |
| MBA BA E.3.3 | Machine Learning for Business | Elective (Business Analytics) | 4 | Machine Learning Basics, Supervised Learning Algorithms, Unsupervised Learning Algorithms, Regression and Classification Models, Deep Learning Fundamentals |
Semester 4
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MBA C.4.1 | Internship Report and Viva-Voce | Core | 4 | Internship Report Writing Guidelines, Data Collection for Internship Report, Analysis and Interpretation of Findings, Presentation Skills for Viva-Voce, Application of Management Concepts |
| MBA C.4.2 | Project Work and Viva-Voce | Core | 8 | Defining Research Problem and Objectives, Project Design and Methodology, Data Collection and Analysis for Project, Report Writing and Documentation, Project Presentation and Viva-Voce |
| MBA BA E.3.4 | Business Intelligence and Data Visualization | Elective (Business Analytics) | 4 | Business Intelligence Concepts, Data Visualization Principles, Dashboard Design and Reporting, BI Tools (e.g., Tableau, Power BI), Data Storytelling, Predictive Modeling in BI |
| MBA BA E.4.1 | Advanced Predictive Analytics | Elective (Business Analytics) | 4 | Time Series Analysis and Forecasting, Text Analytics and Sentiment Analysis, Web Analytics and Digital Marketing, Social Media Analytics, Optimization Techniques for Business, Risk Analytics Models |
| MBA BA E.4.2 | Data Governance and Security | Elective (Business Analytics) | 4 | Data Governance Frameworks, Data Quality Management, Master Data Management (MDM), Data Privacy Regulations (e.g., GDPR, PDPB), Data Security and Compliance, Ethical Considerations in Data |
| MBA BA E.4.3 | Cloud Analytics and IoT | Elective (Business Analytics) | 4 | Cloud Computing Basics for Analytics, Cloud Analytics Platforms (AWS, Azure, GCP), Internet of Things (IoT) Architecture, IoT Data Analytics, Edge Computing and Real-time Analytics, IoT Business Applications |
