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MBA in Business Analytics at University of Lucknow
Lucknow, Uttar Pradesh
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About the Specialization
What is Business Analytics at University of Lucknow Lucknow?
This MBA Business Analytics program at University of Lucknow focuses on equipping students with advanced analytical skills crucial for data-driven decision-making. It integrates core business principles with cutting-edge analytical tools and techniques, addressing the growing demand for analytics professionals across various Indian industries. The program emphasizes practical application and theoretical depth to create well-rounded managers.
Who Should Apply?
This program is ideal for fresh graduates seeking entry into the dynamic field of business analytics, especially those with a background in Mathematics, Statistics, Computer Science, BCA, B.Sc. IT, B.Tech, or B.E. It also caters to working professionals looking to upskill their analytical capabilities and career changers transitioning to data-intensive roles in sectors like e-commerce, finance, and healthcare.
Why Choose This Course?
Graduates of this program can expect to pursue lucrative career paths in India as Data Analysts, Business Intelligence Developers, Analytics Consultants, and Machine Learning Specialists. Entry-level salaries typically range from INR 4-7 LPA, growing significantly with experience. The program aligns with professional certifications in data science and analytics, enhancing growth trajectories in major Indian and multinational corporations.
Student Success Practices
Foundation Stage
Master Quantitative and Analytical Fundamentals- (Semester 1-2)
Dedicate significant time to understanding core concepts in Quantitative Techniques, Research Methodology, and Introduction to Business Analytics. Form study groups to solve problems regularly, focusing on statistical inference, regression, and initial data analysis techniques.
Tools & Resources
NPTEL courses on Statistics and Data Science, Khan Academy, Specific textbooks recommended in the syllabus, R/Python for basic statistical exercises
Career Connection
Strong foundational skills are essential for all advanced analytics roles and form the basis for successful internships and project work in later semesters.
Develop Basic Programming and Data Handling Skills- (Semester 1-2)
Simultaneously, start learning a programming language vital for analytics, preferably Python or R. Practice data cleaning, manipulation, and basic visualization using real-world datasets. Participate in online coding challenges or introductory Kaggle competitions.
Tools & Resources
DataCamp, Coursera (Python for Data Science, R Programming), Jupyter Notebook, Google Colab
Career Connection
Proficiency in programming is a non-negotiable skill for data analysts and data scientists, directly impacting employability and project efficiency.
Engage with Business Case Studies- (Semester 1-2)
Beyond academic learning, actively read and analyze business case studies, especially those with an analytical component. Discuss how data-driven decisions were made or could have been improved. Attend introductory workshops on specific business domains like marketing or finance analytics.
Tools & Resources
Harvard Business Review, IIM case studies, Business newspapers (Economic Times, Livemint), Departmental seminars
Career Connection
This helps in bridging the gap between theoretical knowledge and practical business problem-solving, a critical skill sought by recruiters for analyst roles.
Intermediate Stage
Specialize in Core Analytical Techniques- (Semester 3)
Deep dive into subjects like Data Mining, Machine Learning, and Prescriptive Analytics. Work on mini-projects for each technique, applying them to diverse datasets. Understand the practical implications and limitations of various algorithms for business problems.
Tools & Resources
Scikit-learn, TensorFlow/Keras, RapidMiner, Python libraries (Pandas, NumPy, Matplotlib, Seaborn)
Career Connection
Specialization in these advanced techniques makes you highly competitive for roles requiring specific analytical expertise, such as ML engineer or data scientist.
Develop Strong Data Visualization and BI Skills- (Semester 3)
Focus on mastering Business Intelligence and Data Visualization tools. Create compelling dashboards and reports from complex data. Participate in visualization challenges or build a portfolio of interactive data stories to showcase your skills.
Tools & Resources
Tableau, Microsoft Power BI, Looker Studio (Google Data Studio), D3.js (for web-based visualizations)
Career Connection
Essential for communicating insights effectively to business stakeholders, a key skill for Business Intelligence Developers and Analytics Managers.
Network and Seek Industry Mentorship- (Semester 3)
Actively attend industry webinars, conferences, and networking events (both online and offline) related to business analytics. Connect with professionals on platforms like LinkedIn and seek guidance from industry veterans on career paths and skill development.
Tools & Resources
LinkedIn, Industry-specific forums, Professional meetups in Lucknow/nearby tech hubs
Career Connection
Builds crucial professional networks, potentially leading to internship and job opportunities, and provides valuable insights into industry trends.
Advanced Stage
Execute Capstone and Internship Projects with Excellence- (Semester 4)
Approach your Summer Internship and Capstone Project as real-world consulting assignments. Clearly define the problem, execute rigorous analysis, and present actionable insights. Seek regular feedback from mentors and peers, and document your work meticulously.
Tools & Resources
Project management software (Jira, Asana), Collaboration tools (Slack, Teams), Advanced analytics platforms, Version control (Git)
Career Connection
These projects are your primary resume builders. Strong performance and a well-documented project portfolio significantly enhance placement prospects.
Prepare for Placements and Mock Interviews- (Semester 4)
Start rigorous placement preparation early in the final semester. Practice aptitude tests, technical interviews (SQL, Python, statistics, ML concepts), and HR interviews. Participate in mock interviews with faculty, alumni, and placement cell members.
Tools & Resources
Online platforms for aptitude tests (IndiaBix), LeetCode/HackerRank for coding, Glassdoor for company-specific interview questions, University career services
Career Connection
Direct preparation for securing a good job offer by honing interview skills and technical knowledge relevant to analytics roles.
Develop Data Governance and Ethical AI Understanding- (Semester 4)
Pay close attention to subjects like Data Governance and Ethics. Understand the legal and ethical implications of data handling and AI deployment. Participate in discussions on data privacy regulations (like GDPR, India''''s DPDP Bill) and responsible AI practices.
Tools & Resources
Industry reports on AI ethics, Legal journals, Online courses on data privacy
Career Connection
Crucial for roles involving data strategy, compliance, and leadership, ensuring you can navigate the complex regulatory landscape of data and AI.
Program Structure and Curriculum
Eligibility:
- Any Graduate with 50% marks (45% for SC/ST/OBC/PC) and having Maths/Statistics/Computer Science as a subject at Graduation/10+2 level, or a graduate in BCA/B.Sc. (IT)/B.Tech/B.E. in Computer Science/IT or Equivalent. Selection through Entrance Test (LU)/CUET PG.
Duration: 4 semesters / 2 years
Credits: 96 Credits
Assessment: Internal: 30%, External: 70%
Semester-wise Curriculum Table
Semester 1
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MBA101 | Management Concepts and Organisational Behaviour | Core | 4 | Management Principles, Organizational Behavior, Individual Behavior, Group Dynamics, Leadership, Motivation |
| MBA102 | Quantitative Techniques for Business Decisions | Core | 4 | Probability, Statistical Inference, Regression Analysis, Forecasting, Decision Theory, Linear Programming |
| MBA103 | Managerial Economics | Core | 4 | Demand Analysis, Production and Cost, Market Structures, Pricing Strategies, Macroeconomics, Business Cycles |
| MBA104 | Financial Accounting and Reporting | Core | 4 | Accounting Principles, Financial Statements, Depreciation, Inventory Valuation, Cash Flow Analysis, Ratio Analysis |
| MBA105 | Marketing Management | Core | 4 | Marketing Environment, Consumer Behavior, Market Segmentation, Product Life Cycle, Pricing Decisions, Promotion Mix |
| MBA106 | Introduction to Business Analytics | Core | 4 | Data Science Lifecycle, Data Collection, Descriptive Analytics, Predictive Analytics, Prescriptive Analytics, Big Data Concepts |
Semester 2
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MBA201 | Human Resource Management | Core | 4 | HR Planning, Recruitment and Selection, Training and Development, Performance Management, Compensation, Industrial Relations |
| MBA202 | Financial Management | Core | 4 | Capital Budgeting, Working Capital Management, Cost of Capital, Capital Structure, Dividend Policy, Financial Markets |
| MBA203 | Operations Management | Core | 4 | Production Planning, Inventory Management, Quality Management, Supply Chain Management, Project Management, Lean Operations |
| MBA204 | Research Methodology | Core | 4 | Research Design, Sampling Techniques, Data Collection, Hypothesis Testing, Multivariate Analysis, Report Writing |
| MBA205 | Business Environment & Law | Core | 4 | Economic Environment, Socio-cultural Environment, Legal Framework, Company Law, Consumer Protection, Intellectual Property Rights |
| MBA206 | Data Mining for Business Analytics | Core | 4 | Data Preprocessing, Association Rule Mining, Classification, Clustering, Regression, Text Mining |
Semester 3
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MBA301 | Business Ethics & Corporate Governance | Core | 4 | Ethical Theories, Corporate Social Responsibility, Corporate Governance Principles, Stakeholder Management, Whistleblowing, Global Ethics |
| MBA302 | Business Analytics Applications | Core | 4 | CRM Analytics, Marketing Analytics, Financial Analytics, HR Analytics, Operations Analytics, Healthcare Analytics |
| MBA303 | Machine Learning for Business | Core | 4 | Supervised Learning, Unsupervised Learning, Reinforcement Learning, Neural Networks, Deep Learning, Model Evaluation |
| MBA304 | Prescriptive Analytics and Optimization | Core | 4 | Optimization Models, Linear Programming, Integer Programming, Network Models, Simulation, Decision Trees |
| MBA305 | Business Intelligence and Data Visualization | Core | 4 | BI Architecture, Data Warehousing, ETL Process, Dashboards, Data Storytelling, Visualization Tools (Tableau, Power BI) |
| MBA306 | Big Data Analytics | Core | 4 | Hadoop Ecosystem, Spark, NoSQL Databases, Distributed Computing, Stream Processing, Cloud Analytics |
Semester 4
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MBA401 | Strategic Management | Core | 4 | Strategic Analysis, Strategy Formulation, Strategy Implementation, Corporate Level Strategy, Business Level Strategy, Global Strategy |
| MBA402 | Data Governance and Ethics in Analytics | Core | 4 | Data Privacy, Data Security, Ethical AI, Compliance, GDPR, Data Lifecycle Management |
| MBA403 | Project Management for Analytics | Core | 4 | Project Planning, Agile Methodologies, Risk Management, Resource Allocation, Project Monitoring, Stakeholder Management |
| MBA404 | Summer Internship | Core | 4 | Practical Industry Experience, Report Writing, Presentation Skills, Data Application, Business Problem Solving, Professional Development |
| MBA405 | Capstone Project | Core | 4 | Comprehensive Project, Problem Definition, Data Analysis, Model Development, Solution Implementation, Research Presentation |
| MBA406 | Live Project / Viva Voce | Core | 4 | Real-world Application, Industry Collaboration, Presentation, Defense of Work, Critical Thinking, Communication Skills |
