BUSINESS ANALYTICS
Course overview
The MBA in Business Analytics at Kerala University is designed to equip students with advanced analytical skills, data-driven decision-making expertise, and strategic insights. This program blends core business fundamentals with cutting-edge analytics techniques, preparing graduates for leadership roles in finance, marketing, operations, and AI-driven business strategies.
✅ AICTE & UGC-approved MBA program.
✅ Practical learning with case studies, AI applications, and real-world business challenges.
✅ Hands-on experience with tools like Python, R, Tableau, Power BI, and SQL.
✅ Industry-driven curriculum covering machine learning, predictive analytics, big data, and business intelligence.
✅ Internship & Live Projects with top companies.
What you'll Study
Semester 1
- Principles & Practices of Management
- Organizational Behavior
- Accounting for Managers
- Managerial Economics
- Business Communication
- Business Environment, Ethics & Governance
- Quantitative Techniques
Semester 2
- Operations Research
- Financial & Marketing Management
- Business Law & Research Methodology
- Cybersecurity & Information Systems
- Business Analytics & Data Science
- Statistical Methods Using R & Python
- MOOC Course 1
Semester 3
- Strategic Management
- Big Data Analytics & AI Applications
- Machine Learning & Predictive Analytics
- Marketing Analytics & Consumer Insights
- Operations & Financial Analytics
- Summer Internship (30 Days)
- MOOC Course 2
Semester 4
- Cloud Computing & Big Data for Business
- Business Intelligence & Data Warehousing
- HR & People Analytics
- Capstone Project & Industry Research (60 Days)
Course Structure & Modules
📍 Unit I: Introduction to Business Analytics
✅ Role & Importance of Business Analytics – Data-driven decision-making in enterprises.
✅ Types of Analytics – Descriptive, Diagnostic, Predictive, and Prescriptive Analytics.
✅ Evolution of Business Analytics – From traditional statistics to AI-powered insights.
✅ Key Performance Metrics in Analytics – KPIs, dashboards, and scorecards.
✅ Ethical & Legal Considerations in Analytics – Data privacy, GDPR, compliance issues.
🔹 Key Focus: Understanding core analytics principles, data ethics, and business intelligence frameworks.
📍 Unit II: Data Management & Statistical Analysis
✅ Data Collection & Cleaning – Handling missing values, outliers, and data preprocessing.
✅ Database Management & SQL – Relational databases, cloud storage, and big data processing.
✅ Exploratory Data Analysis (EDA) – Visualizing trends and patterns in data.
✅ Statistical Methods for Business Analytics – Regression, hypothesis testing, probability distributions.
✅ Data Visualization Techniques – Using Tableau, Power BI, and Python for analytics dashboards.
🔹 Key Focus: Extracting, cleaning, and interpreting business data for insights.
📍 Unit III: Predictive Analytics & Machine Learning
✅ Introduction to Machine Learning for Business – Supervised vs. unsupervised learning.
✅ Predictive Modeling Techniques – Regression models, decision trees, and time-series forecasting.
✅ Clustering & Segmentation – Customer segmentation using K-Means & Hierarchical clustering.
✅ Deep Learning & AI in Business Analytics – Neural networks, NLP, and automation.
✅ Case Studies in Predictive Analytics – Credit scoring, fraud detection, demand forecasting.
🔹 Key Focus: Applying machine learning to solve real-world business challenges.
📍 Unit IV: Business Intelligence & Data-Driven Decision Making
✅ Business Intelligence Systems (BI) – SAP, Oracle BI, Microsoft Power BI.
✅ Data Warehousing & ETL Processes – Extract, Transform, Load methodologies.
✅ Optimization Techniques in Business Analytics – Linear programming, Monte Carlo simulation.
✅ AI-Driven Decision Making – Automation in finance, HR, marketing, and operations.
✅ Real-World Applications of BI – Amazon’s recommendation engine, Google Ads optimization.
🔹 Key Focus: Leveraging BI tools and AI-driven insights for business decision-making.
📍 Unit V: Future Trends & Case Studies in Business Analytics
✅ Emerging Trends in Analytics – AI, Blockchain, Digital Twins, IoT-based analytics.
✅ Big Data & Cloud Computing in Analytics – Hadoop, Spark, AWS, and Google Cloud.
✅ Ethical AI & Bias Mitigation in Business Analytics – Fairness in AI-driven decisions.
✅ Industry Case Studies:
📌 Netflix – Personalized recommendation system using AI.
📌 Uber – Surge pricing model based on real-time analytics.
📌 Google – Ad ranking and optimization through machine learning.
📌 Walmart – Inventory optimization using predictive analytics.
🔹 Key Focus: Future-proofing analytics skills with cutting-edge AI & big data trends.
🛠️ Hands-On Learning & Industry Exposure
✅ Internships with top analytics firms – Deloitte, Accenture, TCS, Amazon, Google.
✅ Live projects in AI-driven decision-making – Fraud detection, customer segmentation.
✅ Industry certifications – Google Data Analytics, AWS Cloud Practitioner, Tableau Certified Analyst.
✅ Workshops on AI & Big Data – Hands-on training in Python, R, Power BI, and SQL.
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Your Future Career
The future of Business Analytics is rapidly evolving, with data-driven decision-making becoming essential across industries. As businesses increasingly rely on AI, machine learning, and big data, the demand for skilled professionals in analytics is soaring. Graduates of this course will play a crucial role in transforming business strategies, optimizing operations, and driving innovation through advanced analytics.
Graduate employers
Graduates of Trivandrum International Institute of Management (T-IIM) are highly sought after by leading employers across various industries. Our strong industry connections, global exposure, and focus on practical learning ensure that our students are well-prepared to meet the demands of the corporate world. Here are some of the top sectors and employers where T-IIM graduates have built successful careers
Job roles
Graduates of Trivandrum International Institute of Management (T-IIM) are equipped with the skills, knowledge, and global exposure to excel in a wide range of job roles across industries. Here are some of the key job roles that T-IIM graduates can pursue
- Business Analyst
- Data Scientist
- Marketing Analyst
- Financial Analyst
- Risk Analyst
- Data Engineer
- Business Intelligence Analyst
- Operations Analyst
- Product Analyst
Year Program
Days of summer internship
External Marks ( By the University)
Internships - Criteria Marks Internal
Days of Major Project
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FAQ
Eligibility Criteria ?
- The candidate should have passed the degree from any Indian University, under the regular stream, recognized by the University of Kerala and shall be in the 10+2+3 pattern (or in 10+2+4 pattern). In all the cases the student should have passed the degree examination with not less than 50% marks/equivalent grade (no rounding off allowed)in Part III /core plus complimentary in BA, B.Sc., B.Com. etc., or 50% marks/equivalent grade (no rounding off allowed) in aggregate in case of B.E/ B.Tech, B.Sc. (Agri.) and other 4/5 year degree courses. The candidates, who have passed MA/M.Sc./M.Com.or any other PG Degree recognized by the University of Kerala with 50% of marks/equivalent grade in aggregate, are also eligible for admission. SC/ST, SEBC and differently abled candidates shall be given relaxation as per University rules.
- The candidates should possess a valid score from any one of the entrance examinations conducted by K-MAT, C-MAT or CAT. The scores obtained during the previous academic year alone be considered.
- The provisional rank list for admission to the MBA programme will be prepared on the basis of the score obtained by the candidate in the Entrance Test (80% weightage), Group Discussion (10% weightage) and Interview (10% weightage).
- There will be a representative of the University in the Group discussion and Interview held at the colleges. Dean, Faculty of Management studies will forward the list of representatives to the University and upon approval, the University will intimate colleges.
- Candidates who have passed their Degree or Master’s Degree from other Universities should produce the Eligibility Certificate issued by the University of Kerala (Course Equivalency Certificate) at the time of admission. Only those candidates who produce eligibility certificate and mark lists of Degree or Master’s Degree from other universities at the time of counseling, will be considered for admission.
- Reservation of seats is as per the Government of Kerala and University of Kerala norms from time to time.
What is the MBA in Business Analytics program about?
The MBA in Business Analytics at Kerala University is designed to equip students with data-driven decision-making skills, AI & machine learning applications, and advanced business intelligence techniques. The program integrates core business principles with cutting-edge analytics tools like Python, R, Tableau, and Power BI, preparing graduates for high-demand careers in data analytics, AI, and consulting.
What are the career opportunities after completing this MBA?
Graduates can work in diverse industries such as finance, IT, healthcare, retail, and e-commerce in roles like:
✅ Business Analyst – Data-driven strategy development.
✅ Data Scientist – AI & machine learning model building.
✅ Financial Analyst – Risk management & investment insights.
✅ Marketing Analyst – Customer behavior prediction & campaign optimization.
✅ Operations & Supply Chain Analyst – Process efficiency & forecasting.
📌 Top Recruiters – Deloitte, Accenture, Amazon, Flipkart, TCS, Infosys, KPMG, Microsoft, Google.
What is the scope of Business Analytics in India?
India’s business analytics market is projected to grow at 20% annually, with industries investing heavily in AI-driven business solutions. The demand for data-driven decision-making in sectors like banking, fintech, healthcare, and retail has skyrocketed.
📌 Salary Growth – Freshers: ₹6-10 LPA, Mid-Level: ₹12-18 LPA, Senior Roles: ₹25+ LPA.
📌 Emerging Trends – AI-powered analytics, blockchain in finance, predictive modeling, IoT-driven business insights.
Do I need coding experience for this course?
No prior coding experience is required. The course includes foundational training in:
✅ Python & R for Business Analytics
✅ SQL for Data Analysis
✅ Tableau & Power BI for Data Visualization
✅ Machine Learning & AI Applications
