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B-TECH-MBA in Business Analytics at Shanmugha Arts Science Technology & Research Academy (SASTRA)
Thanjavur, Tamil Nadu
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About the Specialization
What is Business Analytics at Shanmugha Arts Science Technology & Research Academy (SASTRA) Thanjavur?
This Business Analytics program at SASTRA Deemed University focuses on equipping students with advanced analytical skills to transform data into actionable business insights. Recognizing the escalating demand for data-driven decision-makers in the Indian corporate landscape, the program integrates robust B.Tech foundations with specialized MBA knowledge. It emphasizes a blend of statistical methods, machine learning, and business acumen. This unique dual-degree approach ensures graduates are proficient in both technological implementation and strategic business understanding.
Who Should Apply?
This integrated program is ideal for ambitious fresh graduates holding a strong aptitude for mathematics and problem-solving, particularly those aspiring to bridge the gap between technology and business strategy. It also suits working professionals from IT or engineering backgrounds seeking to transition into analytics leadership roles. Individuals looking to gain a comprehensive skill set in data science, predictive modeling, and strategic business application within diverse Indian industries will find this program highly beneficial.
Why Choose This Course?
Graduates of this program can expect to pursue high-demand careers such as Business Analyst, Data Scientist, Analytics Consultant, or Market Research Analyst within India''''s booming data analytics sector. Entry-level salaries typically range from INR 6-12 lakhs per annum, with experienced professionals earning significantly more. The comprehensive curriculum prepares students for roles in IT services, e-commerce, banking, healthcare, and manufacturing, fostering rapid growth trajectories in leading Indian and multinational companies operating in the country.
Student Success Practices
Foundation Stage
Strengthen Programming and Mathematical Logic- (Semester 1-2)
Focus on mastering Python and C++/Java fundamentals taught in the initial semesters. Utilize platforms like HackerRank, LeetCode, and GeeksforGeeks to practice coding challenges, enhancing problem-solving skills crucial for data manipulation and algorithm development.
Tools & Resources
HackerRank, LeetCode, GeeksforGeeks, Python IDLE, C++ Compilers
Career Connection
This foundational strength is vital for later understanding complex analytical models and efficient data processing, directly impacting technical interview performance.
Cultivate Strong Data Structures and Algorithms Acumen- (Semester 1-3)
Dedicate extra effort to Data Structures and Algorithms (DSA). Participate in coding contests and solve problems on platforms such as CodeChef or TopCoder to build robust logical thinking and efficient coding abilities.
Tools & Resources
CodeChef, TopCoder, AlgoExpert, Visualgo
Career Connection
A strong grasp of DSA is indispensable for efficient data handling, optimizing analytical workflows, and excelling in technical rounds for data science and analytics roles.
Develop Effective Study Habits and Peer Learning- (Semester 1-2)
Form study groups to discuss complex topics in Engineering Mathematics, Physics, and Chemistry. Utilize university resources like academic support centers and library materials for comprehensive understanding and collaborative learning.
Tools & Resources
University Library, Academic Support Center, Online forums
Career Connection
Engaging in peer teaching reinforces understanding and builds collaborative skills, which are essential for team-based analytical projects in the corporate world.
Intermediate Stage
Build a Portfolio of Mini-Projects in Core CS/IT- (Semester 3-5)
Apply theoretical knowledge from Database Management Systems, Operating Systems, and Computer Networks by building small, practical projects. Create a GitHub repository to showcase these projects, demonstrating practical application of concepts.
Tools & Resources
GitHub, MySQL/PostgreSQL, Linux Shell, Visual Studio Code
Career Connection
This hands-on experience differentiates resumes and prepares students for capstone projects, offering tangible proof of technical capabilities to potential employers.
Explore Industry-Relevant Tools and Technologies- (Semester 4-6)
Beyond classroom learning, start familiarizing with tools like Tableau, Power BI, and basic SQL/NoSQL databases through online courses or free tutorials. Early exposure to these tools accelerates learning when specialization begins.
Tools & Resources
Tableau Public, Power BI Desktop (Free), Coursera, Udemy
Career Connection
Building familiarity with these tools creates a competitive edge and allows for a smoother transition into advanced Business Analytics subjects and industry roles.
Engage in Departmental Workshops and Seminars- (Semester 3-6)
Actively participate in workshops, technical talks, and guest lectures organized by the Computer Science, IT, or Management departments. These events offer insights into emerging technologies and industry trends.
Tools & Resources
Departmental Announcements, University Events Calendar, LinkedIn for event discovery
Career Connection
Fostering networking opportunities with faculty and professionals through these events can lead to mentorship, internship leads, and a broader understanding of career paths.
Advanced Stage
Undertake Data-Centric Internships and Projects- (Semester 7-9)
Secure internships focusing on data analysis, machine learning, or business intelligence roles to gain real-world experience. Engage in substantial projects using Python/R for statistical modeling and visualization, leveraging actual business data.
Tools & Resources
LinkedIn, Internshala, Company career pages, Kaggle
Career Connection
This practical exposure is critical for understanding industry challenges, building a robust professional portfolio, and significantly enhancing placement opportunities.
Master Advanced Analytics Tools and Techniques- (Semester 7-10)
Deepen proficiency in specialized Business Analytics tools like R, Python (with libraries like Pandas, Scikit-learn), SQL, and visualization tools such as Tableau or Power BI. Practice implementing complex ML algorithms and optimization techniques.
Tools & Resources
RStudio, Anaconda Python, Jupyter Notebooks, SQL Server/PostgreSQL
Career Connection
Mastery of these advanced tools and techniques is non-negotiable for specialized roles like Data Scientist, Machine Learning Engineer, and Analytics Consultant in the Indian market.
Network Strategically and Prepare for Placements- (Semester 8-10)
Attend industry conferences, virtual meetups, and alumni networking events. Actively participate in mock interviews, resume building workshops, and aptitude test preparation offered by the university''''s placement cell.
Tools & Resources
LinkedIn, University Placement Cell, Mock Interview Platforms, Aptitude Prep Websites
Career Connection
Building a strong professional network and being interview-ready are paramount for securing desirable roles in analytics and consulting firms and accelerating career growth.
Program Structure and Curriculum
Eligibility:
- Candidates must pass the 10+2 examination with Physics, Chemistry and Mathematics (PCM) and possess a valid score in JEE (Main) / SASTRA Entrance Examination / Any other equivalent examination as specified by the University.
Duration: 10 semesters / 5 years
Credits: 204 Credits
Assessment: Internal: 40% (Theory), 60% (Lab), 50% (Project), External: 60% (Theory), 40% (Lab), 50% (Project)
Semester-wise Curriculum Table
Semester 1
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| HSB101 | Communication Skills in English | Core | 3 | Language skills, Communication strategies, Oral communication, Written communication, Technical writing |
| MAB101 | Engineering Mathematics – I | Core | 4 | Differential calculus, Integral calculus, Linear algebra, Vector calculus |
| PHB101 | Engineering Physics | Core | 4 | Modern physics, Optics, Electromagnetism, Solid state physics, Quantum mechanics |
| CYB101 | Engineering Chemistry | Core | 4 | Electrochemistry, Thermodynamics, Materials science, Spectroscopy, Environmental chemistry |
| CSB101 | Problem Solving and Python Programming | Core | 3 | Algorithmic thinking, Python basics, Data types, Control flow, Functions |
| CSL101 | Python Programming Lab | Lab | 2 | Hands-on Python, Problem-solving practice, Debugging techniques, Data manipulation, Program development |
| EGB101 | Engineering Graphics | Core | 2 | Orthographic projections, Isometric projections, Sections of solids, Development of surfaces, AutoCAD basics |
| PHL101 | Engineering Physics Lab | Lab | 2 | Basic physics experiments, Measurements and errors, Optical experiments, Electrical circuit analysis, Data analysis |
Semester 2
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| HSB201 | Professional English | Core | 3 | Workplace communication, Presentations skills, Report writing, Email etiquette, Cross-cultural communication |
| MAB201 | Engineering Mathematics – II | Core | 4 | Differential equations, Laplace transforms, Fourier series, Vector calculus, Complex analysis |
| EEB201 | Basic Electrical & Electronics Engineering | Core | 4 | DC/AC circuits, Semiconductor devices, Operational amplifiers, Digital logic gates, Transducers |
| CEB201 | Engineering Mechanics | Core | 3 | Statics of particles, Rigid bodies, Friction, Kinematics, Work and energy |
| CSB201 | Data Structures and Algorithms | Core | 3 | Arrays and lists, Stacks and queues, Trees and graphs, Sorting algorithms, Searching techniques |
| CSL201 | Data Structures Lab | Lab | 2 | Implementing data structures, Algorithm analysis, Dynamic memory allocation, Application development, Debugging exercises |
| MEL201 | Engineering Practices Lab | Lab | 2 | Carpentry, Fitting, Welding, Sheet metal, Plumbing |
| CYL201 | Engineering Chemistry Lab | Lab | 2 | Volumetric analysis, Instrumental analysis, Water quality testing, Corrosion studies, Material characterization |
Semester 3
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MAB301 | Engineering Mathematics – III | Core | 4 | Probability theory, Random variables, Statistical distributions, Regression analysis, Numerical methods |
| CSB301 | Object Oriented Programming | Core | 3 | OOP concepts, Classes and objects, Inheritance, Polymorphism, Exception handling |
| CSL301 | Object Oriented Programming Lab | Lab | 2 | OOP implementation in Java/C++, GUI programming, File I/O operations, Multi-threading, Design patterns |
| MEC301 | Manufacturing Processes | Core | 3 | Metal casting, Forming processes, Machining operations, Welding and joining, Additive manufacturing |
| EIB301 | Microprocessor and Microcontroller | Core | 3 | Microprocessor architecture, Instruction set, Memory interfacing, I/O devices, Microcontroller programming |
| EIL301 | Microprocessor and Microcontroller Lab | Lab | 2 | Assembly language programming, Interfacing peripherals, Embedded system design, Hardware troubleshooting, Sensor integration |
| CSB302 | Database Management Systems | Core | 3 | ER model, Relational model, SQL queries, Normalization, Transaction management |
| CSL302 | Database Management Systems Lab | Lab | 2 | SQL for data manipulation, Database design, Stored procedures, View creation, Report generation |
| HSB301 | Values and Ethics | Core | 3 | Professional ethics, Moral values, Societal impact, Ethical dilemmas, Human values |
Semester 4
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MAB401 | Applied Probability and Statistics | Core | 4 | Probability distributions, Hypothesis testing, Correlation and regression, ANOVA, Time series analysis |
| CSB401 | Operating Systems | Core | 3 | Process management, Memory management, File systems, I/O systems, Deadlocks |
| CSL401 | Operating Systems Lab | Lab | 2 | Linux commands, Shell scripting, Process synchronization, Memory allocation algorithms, System calls |
| ITB401 | Computer Networks | Core | 3 | Network layers, Protocols, IP addressing, Routing algorithms, Network security basics |
| ITL401 | Computer Networks Lab | Lab | 2 | Network configuration, Socket programming, Packet sniffing, Firewall rules, Client-server applications |
| ECB401 | Digital Signal Processing | Core | 3 | Discrete time signals, Z-transform, DFT and FFT, Digital filter design, Multirate signal processing |
| CSB402 | Software Engineering | Core | 3 | SDLC models, Requirements engineering, Software design principles, Testing strategies, Project management |
| OEB401 | Open Elective I | Elective | 3 | Diverse topics based on student choice, Interdisciplinary concepts, Skill development areas, Emerging technologies, Societal relevance |
Semester 5
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MAB501 | Discrete Mathematics | Core | 4 | Logic and proofs, Set theory, Relations and functions, Graph theory, Combinatorics |
| CSB501 | Theory of Computation | Core | 3 | Finite Automata, Regular expressions, Context-Free Grammars, Turing machines, Decidability and Undecidability |
| CSB502 | Compiler Design | Core | 3 | Lexical analysis, Syntax analysis, Intermediate code generation, Code optimization, Runtime environments |
| CSL501 | Compiler Design Lab | Lab | 2 | Lexical analyzer implementation, Parser implementation, Syntax-directed translation, Symbol table management, Code generation |
| GEB501 | General Elective I | Elective | 3 | Advanced programming topics, Emerging technologies, Interdisciplinary applications, Research methodologies, Professional skills |
| ITB501 | Web Technology | Core | 3 | HTML5 and CSS3, JavaScript fundamentals, Client-side frameworks, Server-side scripting, Web security |
| ITL501 | Web Technology Lab | Lab | 2 | Dynamic web page development, Database integration, AJAX and JSON, Web services, Responsive design |
| HSB501 | Professional Ethics | Core | 3 | Engineering ethics, Professional responsibility, Intellectual property, Cyber ethics, Sustainability |
Semester 6
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MAB601 | Operations Research | Core | 4 | Linear programming, Transportation problems, Assignment problems, Queuing theory, Network analysis |
| CSB601 | Artificial Intelligence | Core | 3 | AI agents, Search algorithms, Knowledge representation, Machine learning basics, Natural language processing |
| CSL601 | Artificial Intelligence Lab | Lab | 2 | Implementing search algorithms, Prolog programming, Expert systems, Machine learning libraries, AI project development |
| GEB601 | General Elective II | Elective | 3 | Advanced analytics concepts, Industry-specific applications, Innovation and entrepreneurship, Data privacy and governance, Project management tools |
| ITB601 | Cloud Computing | Core | 3 | Cloud architecture, Service models (IaaS, PaaS, SaaS), Deployment models, Virtualization, Cloud security |
| ITL601 | Cloud Computing Lab | Lab | 2 | AWS/Azure/GCP setup, Cloud resource management, Containerization (Docker), Serverless computing, Cloud storage solutions |
| OEB601 | Open Elective II | Elective | 3 | Various technical fields, Humanities and arts, Management principles, Research methodology, Current affairs and technology |
| CSB602 | Cryptography & Network Security | Core | 3 | Symmetric key cryptography, Asymmetric key cryptography, Hash functions, Digital signatures, Firewalls and IDS |
Semester 7
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| HSB701 | Managerial Economics | Core | 3 | Demand and supply analysis, Production theory, Cost analysis, Market structures, Pricing strategies |
| MAB701 | Advanced Data Analytics | Core | 4 | Statistical inference, Multivariate analysis, Hypothesis testing, Regression techniques, Data visualization |
| BA401 | Fundamentals of Business Analytics | Core | 3 | Analytics concepts, Data types and sources, Business intelligence, Descriptive analytics, Prescriptive analytics |
| BA402 | Data Management for Business Analytics | Core | 3 | SQL and NoSQL databases, Data warehousing, ETL processes, Data governance, Big Data concepts |
| BA403 | Statistical Methods for Business Analytics | Core | 3 | Probability distributions, Sampling techniques, Hypothesis testing, ANOVA, Correlation and regression |
| BA404 | Predictive Analytics | Core | 3 | Linear regression, Logistic regression, Decision trees, Neural networks basics, Time series forecasting |
| BA405 | Data Visualization and Storytelling | Core | 3 | Visualization principles, Dashboard design, Tableau/Power BI, Storytelling with data, Infographic creation |
| BA406 | Business Analytics Lab I | Lab | 2 | R/Python for analytics, Data cleaning and preprocessing, Exploratory data analysis, Statistical software usage, Basic visualization tools |
| BA407 | Internship | Project/Internship | 2 | Industry exposure, Project application, Professional report writing, Teamwork skills, Problem-solving in real-world |
Semester 8
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| BA408 | Optimization and Simulation | Core | 3 | Linear programming, Integer programming, Network models, Simulation modeling, Monte Carlo simulation |
| BA409 | Big Data Technologies | Core | 3 | Hadoop ecosystem, Spark framework, MapReduce, HDFS, NoSQL databases |
| BA410 | Machine Learning for Business Analytics | Core | 3 | Supervised learning, Unsupervised learning, Ensemble methods, Model evaluation, Deployment considerations |
| BA411 | Marketing Analytics | Core | 3 | Customer segmentation, Churn prediction, Campaign optimization, Web analytics, Social media analytics |
| BA412 | Financial Analytics | Core | 3 | Risk analytics, Portfolio optimization, Fraud detection, Credit scoring, Algorithmic trading |
| BA413 | Elective – I (Business Analytics) | Elective | 3 | Supply Chain Analytics, HR Analytics, Healthcare Analytics, Retail Analytics, Operations Analytics |
| BA414 | Business Analytics Lab II | Lab | 2 | Machine learning model implementation, Big data tool usage, Advanced statistical analysis, Case study analysis, Predictive model tuning |
| PRB801 | Project Work – Phase I | Project | 2 | Problem identification, Literature review, Methodology design, Data collection strategies, Project planning |
Semester 9
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| HSB901 | Organizational Behaviour | Core | 3 | Individual behavior, Group dynamics, Leadership theories, Motivation, Organizational culture |
| BA501 | Data Mining for Business Decisions | Core | 3 | Association rule mining, Clustering techniques, Classification algorithms, Text mining, Web mining |
| BA502 | Cloud Computing for Business Analytics | Core | 3 | Cloud analytics services, AWS/Azure/GCP analytics, Data lakes and warehouses in cloud, Cloud data pipelines, Cloud security for data |
| BA503 | Prescriptive Analytics and Decision Making | Core | 3 | Decision trees for prescription, Simulation for decision support, Optimization models, Game theory, A/B testing |
| BA504 | Ethical and Legal Aspects of Data Analytics | Core | 3 | Data privacy regulations (GDPR, etc.), Data security, Algorithmic bias, Ethical AI development, Intellectual property in data |
| BA505 | Elective – II (Business Analytics) | Elective | 3 | Advanced Machine Learning for BA, Deep Learning for BA, IoT Analytics, Geospatial Analytics, Social Network Analytics |
| PRB901 | Project Work – Phase II | Project | 4 | System design, Implementation strategies, Data analysis and interpretation, Intermediate testing, Report writing |
Semester 10
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| HSB1001 | Strategic Management | Core | 3 | Strategic analysis, Strategy formulation, Implementation frameworks, Competitive advantage, Corporate governance |
| BA506 | Natural Language Processing for Business | Core | 3 | Text preprocessing, Sentiment analysis, Topic modeling, Named Entity Recognition, Chatbot development |
| BA507 | Real-time Analytics | Core | 3 | Stream processing, Apache Kafka, Apache Flink/Spark Streaming, Real-time dashboards, Anomaly detection |
| BA508 | Business Intelligence and Data Warehousing | Core | 3 | Data warehousing concepts, OLAP and data cubes, BI tools and dashboards, Reporting strategies, Data quality in BI |
| BA509 | Elective – III (Business Analytics) | Elective | 3 | MLOps and AIOps, Customer Analytics, Digital Transformation & Analytics, Advanced Econometrics, Blockchain Analytics |
| PRB1001 | Project Work – Phase III | Project | 8 | Final implementation, Comprehensive testing, Documentation and reporting, Presentation and defense, Real-world problem solving |
| BA510 | Comprehensive Viva Voce | Viva | 3 | Overall program knowledge, Application of concepts, Critical thinking skills, Communication abilities, Problem-solving aptitude |
