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MBA in Business Analytics at Dayananda Sagar College of Engineering
Bengaluru, Karnataka
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About the Specialization
What is Business Analytics at Dayananda Sagar College of Engineering Bengaluru?
This Business Analytics MBA program at Dayananda Sagar College of Engineering focuses on equipping future managers with cutting-edge analytical skills to drive data-informed decisions. The curriculum is designed to meet the growing demand in the Indian industry for professionals who can leverage data to solve complex business problems and identify strategic opportunities. It uniquely blends core business acumen with advanced analytical techniques.
Who Should Apply?
This program is ideal for fresh graduates with a strong aptitude for quantitative analysis seeking entry into data-driven roles, and for working professionals looking to upskill in analytics to enhance their career progression. It also caters to career changers transitioning into the booming data science and analytics industry within India, requiring a solid foundation in both business and data.
Why Choose This Course?
Graduates of this program can expect to pursue lucrative India-specific career paths such as Business Analyst, Data Scientist, Analytics Consultant, or Market Research Analyst. Entry-level salaries typically range from INR 6-10 lakhs per annum, with experienced professionals commanding significantly higher packages. The program aligns with certifications like Tableau, Power BI, and Python for Data Science, fostering strong growth trajectories in Indian companies.
Student Success Practices
Foundation Stage
Master Core Statistical & Analytical Concepts- (Semester 1-2)
Dedicate time to thoroughly understand foundational business statistics, managerial economics, and the basics of business analytics as covered in Semester 1 and 2. Utilize online platforms for supplemental learning and practice, ensuring a strong base for advanced topics.
Tools & Resources
Khan Academy Statistics, Coursera/edX for introductory R/Python, NPTEL lectures on Business Statistics
Career Connection
A solid conceptual understanding is crucial for correctly interpreting data, building robust models, and articulating insights, directly impacting your ability to excel in analytical roles.
Develop Proficiency in Spreadsheet & Basic BI Tools- (Semester 1-2)
Actively participate in Business Analytics Labs and practice extensively with tools like Microsoft Excel for data manipulation, cleaning, and basic visualization. Explore self-paced tutorials for introductory Power BI or Tableau to get a head start on data dashboarding.
Tools & Resources
Microsoft Excel advanced functions, Power BI Desktop (free version), Tableau Public, YouTube tutorials for basic dashboarding
Career Connection
Hands-on experience with these fundamental tools is a baseline expectation for any business analyst role in India, allowing you to efficiently handle and present data.
Engage in Peer Learning & Case Study Analysis- (Semester 1-2)
Form study groups to discuss complex business scenarios and apply learned analytical techniques through case studies. Regularly participate in classroom discussions, challenging assumptions and exploring multiple solutions. This improves problem-solving and communication skills.
Tools & Resources
Harvard Business Review (academic access), IIM/ISB case study repositories, Team collaboration tools
Career Connection
Collaborative problem-solving and critical thinking developed through case studies are highly valued in consulting and analytical project teams, enhancing your employability.
Intermediate Stage
Build a Portfolio of Practical Analytics Projects- (Semester 3-4)
Beyond coursework, undertake small personal projects or participate in Kaggle competitions using public datasets. Focus on applying predictive modeling, big data tools, and data visualization techniques learned in Semesters 3-4, documenting your process and insights thoroughly.
Tools & Resources
Kaggle.com, GitHub for project showcase, Google Colab/Jupyter Notebooks, VTU MBA Syllabus examples
Career Connection
A strong project portfolio demonstrates practical skills to Indian recruiters, making you stand out for roles in data science, advanced analytics, and machine learning engineering.
Network with Industry Professionals & Alumni- (Semester 3-4)
Attend industry workshops, webinars, and conferences (virtual or local in Bengaluru). Connect with DSCE alumni and professionals in Business Analytics on platforms like LinkedIn. Seek mentorship and insights into current industry trends and career paths in India.
Tools & Resources
LinkedIn, Professional analytics meetups in Bengaluru, Industry association events
Career Connection
Networking opens doors to internship and placement opportunities, provides valuable career guidance, and helps you understand specific industry requirements for analytics professionals.
Deepen Programming Skills in Python/R for Analytics- (Semester 3-4)
While the labs provide an introduction, dedicate extra time to master Python or R for advanced data manipulation, statistical modeling, and machine learning. Complete online specializations or certifications to gain expertise in libraries like Pandas, NumPy, Scikit-learn, and ggplot2.
Tools & Resources
DataCamp/Udemy/Coursera Python/R specializations, LeetCode/HackerRank for coding practice, Official documentation of libraries
Career Connection
Proficiency in Python/R is a core requirement for almost all advanced analytics and data science roles in top Indian companies and MNCs, significantly boosting your technical profile.
Advanced Stage
Excel in Internship & Capstone Project- (Semester 4)
Treat your internship and final project as a real-world analytics assignment. Proactively identify impactful problems, propose data-driven solutions, and contribute significantly. This is your primary opportunity to apply all learned skills and make a tangible difference to an organization, preferably in the Business Analytics domain.
Tools & Resources
Company-specific data/tools, Mentors/Supervisors guidance, Academic resources for project methodology
Career Connection
A successful internship often leads to pre-placement offers, and a well-executed capstone project is a strong talking point in interviews, demonstrating problem-solving and execution capabilities.
Prepare for Technical & Behavioral Interviews- (Semester 4)
Practice coding challenges (Python/R), statistical concepts, and machine learning algorithms. Simultaneously, work on soft skills like communication, problem-solving, and critical thinking for behavioral interviews. Participate in mock interviews with faculty or career services.
Tools & Resources
GeeksforGeeks, Interviewer.io for mock interviews, DSCE Career Guidance Cell, Books on interview preparation
Career Connection
Thorough preparation for both technical and behavioral aspects ensures you confidently navigate the placement process, maximizing your chances of securing a desirable analytics role in India.
Stay Updated with Emerging Technologies & Trends- (Throughout the program, intensifying in Semester 4)
Regularly follow industry blogs, research papers, and news from leading analytics firms and tech giants. Understand new tools, techniques (e.g., MLOps, explainable AI), and their applications in business. This demonstrates intellectual curiosity and readiness for continuous learning.
Tools & Resources
Towards Data Science (Medium), Analytics India Magazine, KDNuggets, Google AI Blog
Career Connection
Staying current is vital in the fast-evolving analytics field. It shows prospective employers your commitment to growth and ability to adapt, which is critical for long-term career success in Indian tech and analytics sectors.
Program Structure and Curriculum
Eligibility:
- Bachelor''''s Degree with 50% aggregate marks (45% for SC/ST/Category-I candidates of Karnataka) from a recognized university, with a valid score in PGCET/CMAT/KMAT/MAT/XAT/ATMA/CAT.
Duration: 2 years (4 Semesters)
Credits: 100 Credits
Assessment: Internal: 50%, External: 50%
Semester-wise Curriculum Table
Semester 1
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 22MBA11 | Management and Organizational Behavior | Core | 4 | Management Concepts and Functions, Organizational Behavior Foundations, Personality, Perception and Learning, Motivation and Leadership Theories, Group Dynamics and Team Building |
| 22MBA12 | Managerial Economics | Core | 4 | Nature and Scope of Managerial Economics, Demand and Supply Analysis, Production and Cost Analysis, Market Structures and Pricing Strategies, Capital Budgeting and Risk Analysis |
| 22MBA13 | Accounting for Managers | Core | 4 | Financial Accounting Principles, Preparation of Financial Statements, Cost Accounting Concepts, Budgeting and Variance Analysis, Fund Flow and Cash Flow Statements |
| 22MBA14 | Business Statistics | Core | 4 | Data Collection and Presentation, Measures of Central Tendency and Dispersion, Probability and Probability Distributions, Sampling and Hypothesis Testing, Correlation and Regression Analysis |
| 22MBA15 | Business and Professional Communication | Core | 4 | Fundamentals of Business Communication, Oral Communication Skills, Written Communication and Business Correspondence, Presentation Strategies and Techniques, Report Writing and Documentation |
| 22MBA16 | Business Environment and Law | Core | 4 | Economic Environment and Policies, Political, Legal and Socio-cultural Environment, Technological Environment and Ethics, Corporate Governance and Social Responsibility, Legal Aspects of Business (Contracts, Companies Act) |
| 22MBAL17 | Business Analytics Lab - I | Lab | 2 | Introduction to Analytics Tools (Excel, R/Python basics), Data Cleaning and Pre-processing, Descriptive Statistics Implementation, Data Visualization Techniques, Exploratory Data Analysis |
Semester 2
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 22MBA21 | Marketing Management | Core | 4 | Marketing Concepts and Philosophies, Consumer Behavior and Market Segmentation, Product and Brand Management, Pricing Strategies and Decisions, Promotion and Distribution Channels |
| 22MBA22 | Financial Management | Core | 4 | Financial System and Capital Markets, Time Value of Money and Valuation, Capital Budgeting Decisions, Working Capital Management, Dividend Policy and Cost of Capital |
| 22MBA23 | Human Resource Management | Core | 4 | HR Planning and Job Analysis, Recruitment and Selection Strategies, Training, Development and Performance Appraisal, Compensation and Employee Benefits, Industrial Relations and Labor Welfare |
| 22MBA24 | Operations Management | Core | 4 | Operations Strategy and Productivity, Process Design and Layout Planning, Inventory Management Techniques, Quality Management and TQM, Supply Chain Management Fundamentals |
| 22MBA25 | Research Methods | Core | 4 | Research Design and Problem Formulation, Data Collection Methods (Primary & Secondary), Sampling Techniques and Ethics in Research, Data Analysis (Parametric & Non-Parametric Tests), Report Writing and Presentation |
| 22MBA26 | Entrepreneurship and Startup Management | Core | 4 | Concept of Entrepreneurship and Innovation, Business Idea Generation and Opportunity Evaluation, Business Plan Preparation and Funding Sources, Startup Ecosystem and Legal Aspects, Marketing and Growth Strategies for Startups |
| 22MBAL27 | Business Analytics Lab - II | Lab | 2 | Introduction to Predictive Analytics, Regression Analysis with Software, Classification Techniques (Logistic Regression, Decision Trees), Time Series Forecasting Basics, Introduction to Data Mining Concepts |
Semester 3
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 22MBA3BA1 | Applied Business Analytics | Elective | 4 | Data Warehousing and Data Mining, Predictive Modeling and Business Intelligence, Machine Learning Algorithms in Business, Data-Driven Decision Making, Business Process Automation using Analytics |
| 22MBA3BA2 | Big Data Analytics | Elective | 4 | Introduction to Big Data Concepts, Hadoop Ecosystem (HDFS, MapReduce), Spark Framework for Data Processing, NoSQL Databases (MongoDB, Cassandra), Real-time Data Processing and Stream Analytics |
| 22MBA3BA3 | Data Visualization for Business | Elective | 4 | Principles of Effective Data Visualization, Choosing Appropriate Chart Types, Dashboard Design and Storytelling with Data, Introduction to Visualization Tools (Tableau, Power BI), Interactive Visualizations and Infographics |
Semester 4
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 22MBA4BA4 | AI and Machine Learning in Business | Elective | 4 | Fundamentals of Artificial Intelligence, Supervised and Unsupervised Learning, Deep Learning Basics and Neural Networks, Natural Language Processing for Business, Ethical Considerations in AI/ML |
| 22MBA4BA5 | Advanced Business Analytics Tools | Elective | 4 | Advanced R and Python for Analytics, Statistical Modeling and Econometrics, Text Analytics and Sentiment Analysis, Web Analytics and Social Media Analytics, Cloud-based Analytics Platforms (AWS, Azure) |
| 22MBA4I6 | Internship and Report | Internship | 4 | Industry Exposure and Practical Application, Problem Identification and Solution Design, Data Collection and Analysis in Real-world Setting, Project Documentation and Report Writing, Presentation of Internship Findings |
| 22MBA4P7 | Project Work | Project | 10 | Comprehensive Business Problem Definition, Extensive Literature Review, Advanced Data Collection and Methodologies, In-depth Data Analysis and Interpretation, Final Project Report and Viva-Voce |
