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M-B-A in Business Analytics at Devi Ahilya Vishwavidyalaya
Indore, Madhya Pradesh
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About the Specialization
What is Business Analytics at Devi Ahilya Vishwavidyalaya Indore?
This Business Analytics program at Devi Ahilya Vishwavidyalaya focuses on equipping future managers with cutting-edge analytical skills to drive data-informed decision-making. In the rapidly evolving Indian business landscape, where data is becoming a strategic asset, this program emphasizes practical application of tools and techniques to solve real-world problems. It integrates core business knowledge with advanced analytics, statistics, and machine learning, ensuring graduates are prepared for the high demand in various sectors.
Who Should Apply?
This program is ideal for fresh graduates from diverse backgrounds (engineering, commerce, science) seeking entry into the analytics domain. It also caters to working professionals who aspire to upskill in data analytics for career advancement or to transition into roles that require strong analytical capabilities. Candidates with a keen interest in data, problem-solving, and a foundational understanding of mathematics will find this specialization highly rewarding.
Why Choose This Course?
Graduates of this program can expect to pursue lucrative India-specific career paths such as Data Analyst, Business Intelligence Developer, Predictive Modeler, Analytics Consultant, and Machine Learning Engineer in sectors like e-commerce, banking, healthcare, and IT. Entry-level salaries typically range from INR 4-7 LPA, growing significantly with experience. The program aligns with industry demand for professionals who can translate complex data into actionable business insights, fostering rapid career growth in Indian companies.
Student Success Practices
Foundation Stage
Master Quantitative and Business Fundamentals- (undefined)
Dedicate significant time to thoroughly grasp subjects like Quantitative Techniques, Accounting, Economics, and Business Analytics Fundamentals. Form study groups with peers to clarify concepts, solve problems, and discuss business cases. Utilize online platforms like Khan Academy or NPTEL for supplementary learning in statistics and economics.
Tools & Resources
Textbooks, University Library, Khan Academy, NPTEL, Study Groups
Career Connection
A strong foundation is crucial for advanced analytics. This ensures you build robust models and interpret business data correctly, which is vital for roles like Junior Data Analyst or BI Intern.
Develop Foundational Software Skills- (undefined)
Actively engage with Computer Applications in Management labs to gain proficiency in MS Excel and SQL basics. Practice regularly beyond classroom assignments. Seek out free online tutorials on platforms like Coursera (for Excel) and SQLZoo (for SQL) to build practical application skills early on.
Tools & Resources
MS Excel, SQL, Coursera, SQLZoo, Lab Sessions
Career Connection
Proficiency in Excel and SQL is a baseline requirement for almost all data-centric roles in India. Early mastery opens doors for better internships and entry-level analyst positions.
Enhance Communication and Presentation Skills- (undefined)
Participate actively in skill development workshops focused on communication, group discussions, and presentations. Practice public speaking by volunteering for presentations in class. Join Toastmasters International or similar clubs if available to refine your articulation and delivery.
Tools & Resources
Skill Development workshops, Mock GD/Interview sessions, Toastmasters (if applicable)
Career Connection
Analysts frequently need to present complex data insights to non-technical stakeholders. Strong communication skills are essential for career progression and leadership roles in Indian corporates.
Intermediate Stage
Deep Dive into Core Analytics Tools (Python, Tableau)- (undefined)
Beyond coursework, dedicate consistent effort to mastering Python for Data Science and data visualization tools like Tableau or Power BI. Work on mini-projects using real-world datasets from Kaggle or data.gov.in. Aim for certifications in these tools if possible.
Tools & Resources
Python (Pandas, NumPy, Matplotlib, Scikit-learn), Tableau/Power BI, Kaggle, data.gov.in, Online certifications
Career Connection
These tools are industry standards. Proficiency directly translates into higher demand for roles like Data Scientist, ML Engineer, and Business Intelligence Developer in Indian IT and analytics firms.
Build a Portfolio of Analytical Projects- (undefined)
Start building a personal portfolio by applying learned techniques to solve diverse business problems. These could be academic projects, independent analyses, or contributions to open-source data projects. Document your methodologies and insights clearly on platforms like GitHub or LinkedIn.
Tools & Resources
GitHub, LinkedIn, Kaggle, Real-world datasets, Personal blog/website
Career Connection
A strong project portfolio showcases practical skills and problem-solving ability, significantly boosting your resume for placements and attracting attention from Indian tech and consulting companies.
Network with Industry Professionals and Participate in Competitions- (undefined)
Attend industry seminars, webinars, and workshops in Indore and nearby cities. Connect with alumni and professionals on LinkedIn. Participate in hackathons and data science competitions on platforms like Analytics Vidhya or HackerRank to gain exposure and test your skills against peers.
Tools & Resources
LinkedIn, Industry events, Analytics Vidhya, HackerRank, University career fair
Career Connection
Networking can lead to mentorship, internship opportunities, and insider knowledge. Competition participation validates your skills and can lead to direct recruitment by leading Indian companies.
Advanced Stage
Specialize and Undertake an Impactful Capstone Project- (undefined)
Choose your electives strategically based on your career interests (e.g., Financial Analytics, Marketing Analytics). Invest deeply in your Capstone Project, aiming to solve a complex business problem for an organization. Seek industry mentorship for your project to ensure its relevance and impact.
Tools & Resources
Elective courses, Industry mentors, Research papers, Advanced analytics software
Career Connection
A well-executed, impactful capstone project can be your strongest selling point in interviews, demonstrating your ability to deliver business value using analytics, highly valued by Indian employers.
Focus on Ethical AI and Data Governance- (undefined)
Beyond theoretical understanding, consider how ethical principles and data governance frameworks apply in real-world scenarios in India. Explore specific regulations like India''''s upcoming Data Protection Bill. Engage in discussions and case studies on responsible AI deployment.
Tools & Resources
Regulatory documents, AI ethics guidelines, Case studies, Professional forums
Career Connection
As data privacy and ethical AI become paramount in India, professionals with a strong grasp of these concepts are highly sought after, especially in compliance, risk, and strategic roles in large organizations.
Prepare for Placements with Mock Interviews and Case Studies- (undefined)
Actively participate in placement preparatory activities, including mock interviews (technical and HR), group discussions, and case study solving sessions. Practice explaining your projects and analytical approaches clearly. Focus on behavioral aspects and problem-solving aptitude expected by Indian companies.
Tools & Resources
Career Services, Mock interview panels, Case study books, Industry-specific interview guides
Career Connection
Thorough preparation ensures you can articulate your value proposition effectively, leading to successful placements in top-tier analytics firms, consulting companies, and technology giants in India.
Program Structure and Curriculum
Eligibility:
- Graduation in any discipline with minimum 50% aggregate marks (45% for SC/ST/OBC (non-creamy layer) candidates)
Duration: 2 years (4 semesters)
Credits: 108 Credits
Assessment: Internal: 40% (for theory subjects), External: 60% (for theory subjects)
Semester-wise Curriculum Table
Semester 1
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MBABA1C1 | Managerial Economics | Core | 4 | Basic economic concepts, Demand and Supply analysis, Production and Cost analysis, Market structures and pricing, Macroeconomics overview |
| MBABA1C2 | Accounting for Managers | Core | 4 | Financial accounting fundamentals, Cost accounting principles, Management accounting concepts, Financial statement analysis, Budgeting and budgetary control |
| MBABA1C3 | Organizational Behavior | Core | 4 | Foundations of Organizational Behavior, Individual behavior and perception, Motivation and leadership theories, Group dynamics and conflict management, Organizational culture and change |
| MBABA1C4 | Quantitative Techniques for Business Decisions | Core | 4 | Linear programming, Transportation and Assignment problems, Queuing theory, Decision theory under uncertainty, Network analysis (PERT/CPM) |
| MBABA1C5 | Marketing Management | Core | 4 | Marketing concepts and environment, Market segmentation and targeting, Product and brand management, Pricing strategies, Promotion and distribution channels |
| MBABA1C6 | Business Analytics Fundamentals | Core | 4 | Introduction to Business Analytics, Data types and sources, Data collection and cleansing, Descriptive analytics techniques, Introduction to data visualization |
| MBABA1S1 | Skill Development – I | Skill | 2 | Communication skills, Presentation techniques, Group discussion strategies, Interview skills, Professional ethics |
| MBABA1L1 | Computer Applications in Management – Lab I | Lab | 2 | MS Office applications (Word, Excel, PowerPoint), Advanced Excel features for data handling, Basic internet applications, Data security concepts, Cloud computing basics |
Semester 2
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MBABA2C1 | Human Resource Management | Core | 4 | HR planning and strategy, Recruitment and selection, Training and development, Performance appraisal systems, Compensation and benefits, Industrial relations |
| MBABA2C2 | Financial Management | Core | 4 | Capital budgeting decisions, Working capital management, Capital structure theories, Dividend policy, Sources of finance, Financial markets |
| MBABA2C3 | Operations Management | Core | 4 | Production planning and control, Inventory management models, Quality management techniques, Supply chain management, Project management basics, Facility layout and location |
| MBABA2C4 | Research Methodology | Core | 4 | Research design and types, Data collection methods (primary/secondary), Sampling techniques, Data analysis and interpretation, Hypothesis testing, Research report writing |
| MBABA2C5 | Business Intelligence | Core | 4 | Introduction to Business Intelligence, Data warehousing concepts, ETL processes, OLAP and reporting tools, Dashboard design, BI applications in business |
| MBABA2C6 | Data Mining for Business Analytics | Core | 4 | Introduction to data mining, Classification techniques, Clustering algorithms, Association rule mining, Predictive modeling, Text mining basics |
| MBABA2S1 | Skill Development – II | Skill | 2 | Advanced communication strategies, Negotiation skills, Stress and time management, Corporate etiquette, Teamwork and collaboration |
| MBABA2L1 | Computer Applications in Management – Lab II | Lab | 2 | Advanced Excel for data analysis, Introduction to SQL queries, Data visualization tools (Tableau/Power BI), Statistical software basics (R/Python environment setup), Database management concepts |
Semester 3
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MBABA3C1 | Applied Econometrics | Core | 4 | Introduction to Econometrics, Regression analysis (OLS), Time series analysis, Panel data methods, Forecasting models, Econometric software applications |
| MBABA3C2 | Machine Learning for Business | Core | 4 | Introduction to Machine Learning, Supervised and Unsupervised learning, Regression and Classification algorithms, Ensemble methods, Model evaluation and selection, Introduction to Deep Learning |
| MBABA3C3 | Data Visualization and Storytelling | Core | 4 | Principles of effective data visualization, Types of charts and graphs, Dashboard design best practices, Storytelling with data, Tools like Tableau/Power BI, Interactive visualizations |
| MBABA3C4 | Big Data Technologies | Core | 4 | Introduction to Big Data, Hadoop ecosystem (HDFS, MapReduce), Spark framework, NoSQL databases, Data ingestion and processing, Real-time analytics |
| MBABA3C5 | Python for Data Science | Core | 4 | Python programming fundamentals, Data structures in Python, NumPy for numerical computing, Pandas for data manipulation, Matplotlib and Seaborn for visualization, Introduction to Scikit-learn |
| MBABA3C6 | Prescriptive Analytics | Core | 4 | Optimization techniques, Decision modeling and analysis, Simulation methods, A/B testing, Heuristic approaches, Applications of operations research |
| MBABA3S1 | Skill Development – III | Skill | 2 | Advanced problem-solving techniques, Critical thinking and analytical skills, Innovation and creativity, Entrepreneurial mindset development, Ethical considerations in analytics |
| MBABA3E1.1 | Financial Analytics | Elective | 2 | Financial modeling, Risk analytics and management, Portfolio optimization, Algorithmic trading concepts, Fintech applications, Market prediction using data |
| MBABA3E1.2 | Marketing Analytics | Elective | 2 | Consumer behavior analytics, Digital marketing analytics, Campaign optimization, Customer lifetime value modeling, Market mix modeling, Sales forecasting |
| MBABA3E1.3 | HR Analytics | Elective | 2 | Workforce planning and analytics, Talent acquisition and retention analytics, Performance analytics, Employee engagement and attrition prediction, HR dashboards and reporting, HR metrics |
| MBABA3E1.4 | Supply Chain Analytics | Elective | 2 | Demand forecasting in SCM, Inventory optimization, Logistics and transportation analytics, Supplier performance analysis, Network design and optimization, Risk management in supply chain |
| MBABA3E1.5 | Health Care Analytics | Elective | 2 | Healthcare data sources and types, Predictive modeling in health, Patient outcome analytics, Clinical decision support systems, Public health analytics, Healthcare operational efficiency |
| MBABA3E1.6 | Energy and Utility Analytics | Elective | 2 | Smart grid analytics, Energy consumption forecasting, Asset management in utilities, Demand response analysis, Renewable energy analytics, Operational efficiency in energy sector |
Semester 4
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MBABA4C1 | AI and Cognitive Computing | Core | 4 | Introduction to Artificial Intelligence, Advanced Machine Learning concepts, Natural Language Processing, Computer Vision fundamentals, Robotics and automation, Cognitive systems and applications |
| MBABA4C2 | Ethical AI and Data Governance | Core | 4 | Ethics in AI and data science, Data privacy regulations (GDPR, Indian laws), Algorithmic bias and fairness, Responsible AI development, Data security and compliance, Data governance frameworks |
| MBABA4C3 | Cloud Computing for Analytics | Core | 4 | Introduction to Cloud Computing, Cloud platforms (AWS, Azure, GCP), Cloud storage solutions, Big Data services on cloud, Serverless computing, DevOps for analytics |
| MBABA4C4 | Capstone Project/Dissertation | Project | 8 | Problem identification and definition, Literature review and research design, Data collection and analysis, Solution development and implementation, Report writing and presentation, Project management skills |
| MBABA4S1 | Skill Development – IV | Skill | 2 | Advanced negotiation and persuasion, Leadership and team management, Strategic thinking and planning, Global business awareness, Conflict resolution |
| MBABA4L1 | Analytics Tools and Techniques Lab | Lab | 2 | Advanced Tableau/Power BI applications, R/Python for Machine Learning algorithms, Advanced SQL and NoSQL database operations, Cloud-based analytics platform hands-on, Data pipeline and ETL tools |
