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B-COM-REGULAR in Business Analytics at St. Joseph's College of Commerce (Autonomous)
Bengaluru, Karnataka
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About the Specialization
What is Business Analytics at St. Joseph's College of Commerce (Autonomous) Bengaluru?
This B.Com (Business Analytics) program at St. Joseph''''s College of Commerce, Bengaluru, focuses on equipping students with crucial data analysis and business intelligence skills. In the rapidly digitizing Indian economy, businesses heavily rely on data-driven insights for strategic decisions, making this program highly relevant. Its interdisciplinary approach combines commerce principles with advanced analytical tools to meet evolving industry demands.
Who Should Apply?
This program is ideal for commerce graduates or 10+2 students with an inclination towards numbers and logical reasoning, seeking entry into high-growth analytics roles. It also suits aspiring entrepreneurs who want to leverage data for business success, or individuals looking to transition into data-centric roles from traditional commerce backgrounds. Strong analytical aptitude and basic computer literacy are beneficial prerequisites.
Why Choose This Course?
Graduates of this program can expect to pursue dynamic career paths such as Business Analyst, Data Analyst, Market Research Analyst, Financial Analyst, or Consultant in various Indian companies and MNCs. Entry-level salaries typically range from INR 4-7 lakhs per annum, with significant growth potential as experience and expertise develop. The curriculum also prepares students for further professional certifications in analytics or postgraduate studies.
Student Success Practices
Foundation Stage
Master Foundational Analytical Tools and Concepts- (Semester 1-2)
Focus on thoroughly understanding core business analytics concepts, statistics, and introductory programming (Python). Actively participate in class, solve textbook problems, and use online tutorials to strengthen logic. Seek help from faculty or peers for challenging concepts early on.
Tools & Resources
Python IDEs (Jupyter Notebook, VS Code), Statistical software like R (optional), Online platforms (Khan Academy, Coursera)
Career Connection
A strong foundation in these areas is crucial for building complex analytical models later, opening doors to junior data analyst or business intelligence roles.
Develop Strong Communication and Presentation Skills- (Semester 1-2)
Engage in group assignments, deliver presentations, and actively participate in debates and discussions. Focus on clearly articulating business problems and analytical findings. Join college clubs focused on public speaking or debate to hone these skills.
Tools & Resources
PowerPoint, Google Slides, Toastmasters International (if available), College communication workshops
Career Connection
Effective communication is vital for presenting data insights to non-technical stakeholders, a key skill for any successful business analyst.
Build a Strong Network and Explore Industry Basics- (Semester 1-2)
Attend introductory webinars, workshops, and guest lectures by industry professionals. Connect with seniors and alumni on LinkedIn to understand their career paths and seek guidance. Read business newspapers and industry reports to grasp current trends.
Tools & Resources
LinkedIn, College alumni network events, Industry news portals (e.g., Livemint, Business Standard), NASSCOM reports
Career Connection
Early networking can lead to mentorship opportunities, internship leads, and a better understanding of industry expectations for future roles.
Intermediate Stage
Apply Data Skills to Real-World Mini-Projects- (Semester 3-5)
Beyond coursework, initiate personal mini-projects using open datasets (e.g., Kaggle, UCI Machine Learning Repository). Focus on skills learned in RDBMS, Advanced Excel, and Python for Data Science. Collaborate with peers on these projects to simulate team environments.
Tools & Resources
Kaggle, GitHub, SQL databases (MySQL, PostgreSQL), Tableau/Power BI trial versions, Project management tools (Trello, Asana)
Career Connection
A portfolio of practical projects demonstrates hands-on experience and problem-solving abilities to recruiters, significantly boosting internship and placement chances.
Seek Meaningful Internships and Industry Exposure- (Semester 4-5)
Actively search for internships in analytics, finance, or marketing departments of companies. Focus on gaining exposure to real business problems and corporate culture. Apply learnings from subjects like Marketing Analytics and Financial Management.
Tools & Resources
College placement cell, LinkedIn Jobs, Internshala, Company career pages, Resume building workshops
Career Connection
Internships provide invaluable practical experience, industry contacts, and often lead to pre-placement offers, accelerating career entry.
Deepen Specialization and Participate in Competitions- (Semester 4-5)
Choose electives wisely based on career interests (e.g., Financial Analytics, HR Analytics). Participate in business analytics hackathons, case study competitions, and quizzes organized by colleges or industry bodies. This sharpens critical thinking and showcases skills.
Tools & Resources
Analytics Vidhya, Datacamp, Industry-specific forums, College competition announcements
Career Connection
Winning or participating in competitions enhances your resume, provides networking opportunities, and validates your specialized skills to potential employers.
Advanced Stage
Execute a Comprehensive Capstone Project/Internship- (Semester 6)
Devote significant effort to the final semester''''s project work or extended internship. Identify a real business problem, apply advanced analytical techniques (Machine Learning, Big Data), and deliver actionable insights. Document the process meticulously and prepare a professional presentation.
Tools & Resources
Advanced analytics software (Python/R, SQL), Cloud platforms (AWS, Azure, GCP), Project management methodologies, Mentorship from faculty/industry experts
Career Connection
A well-executed capstone project or internship can serve as your primary portfolio piece, demonstrating end-to-end analytical capability and securing high-value placements.
Master Interview Skills and Professional Branding- (Semester 6)
Attend mock interview sessions and workshops focusing on technical, behavioral, and case study questions relevant to analytics roles. Refine your resume and LinkedIn profile to highlight projects, skills, and certifications. Network strategically for placement opportunities.
Tools & Resources
College placement cell, Online interview preparation platforms (e.g., LeetCode, Glassdoor), LinkedIn for professional networking
Career Connection
Strong interview performance and a polished professional brand are critical for converting opportunities into successful job offers.
Explore Advanced Certifications and Continuous Learning- (Semester 6 and beyond)
Consider pursuing industry-recognized certifications in specific analytics tools (e.g., Tableau Certified Associate, Microsoft Certified: Azure Data Scientist Associate) or domains (e.g., Google Analytics Certification). Stay updated with emerging trends like AI and Generative AI in business analytics.
Tools & Resources
Coursera, edX, Udemy, Official vendor certification programs, Industry blogs & research papers
Career Connection
Continuous learning and advanced certifications demonstrate initiative and specialized expertise, enabling faster career progression and higher earning potential in the dynamic analytics field.
Program Structure and Curriculum
Eligibility:
- Passed 10+2 / Pre-University Course or equivalent with 40% marks in aggregate.
Duration: 6 semesters / 3 years
Credits: 134 Credits
Assessment: Internal: 30%, External: 70%
Semester-wise Curriculum Table
Semester 1
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 23BA101 | Language I - English | Core | 3 | Communication Skills, Literary Analysis, Vocabulary Development, Grammar & Usage, Report Writing |
| 23BA102 | Language II - Kannada/Hindi/Sanskrit/French | Core | 3 | Grammar & Syntax, Literature & Culture, Basic Communication, Writing Skills, Translation & Comprehension |
| 23BA103 | Fundamentals of Business Analytics | Core | 4 | Introduction to Business Analytics, Data Types & Sources, Data Collection & Preparation, Descriptive Analytics, Prescriptive & Predictive Analytics, Business Intelligence Concepts |
| 23BA104 | Financial Accounting | Core | 4 | Accounting Principles, Journal, Ledger, Trial Balance, Final Accounts of Sole Proprietor, Depreciation Accounting, Partnership Accounts, Accounting Standards |
| 23BA105 | Fundamentals of Marketing | Core | 4 | Marketing Concepts, Marketing Environment, Consumer Behavior, Market Segmentation & Targeting, Marketing Mix (4 Ps), Product Life Cycle |
| 23BA106 | Computers for Business | Core | 4 | Computer Fundamentals, Operating Systems, MS Office Applications, Internet & E-commerce, Cyber Security Basics, Data Representation |
Semester 2
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 23BA201 | Language I - English | Core | 3 | Advanced Communication, Business Correspondence, Presentation Skills, Group Discussions, Report Writing & Drafting |
| 23BA202 | Language II - Kannada/Hindi/Sanskrit/French | Core | 3 | Advanced Grammar & Usage, Literary Criticism, Public Speaking, Cultural Narratives, Creative Writing |
| 23BA203 | Business Statistics | Core | 4 | Data Collection & Presentation, Measures of Central Tendency & Dispersion, Probability Theory, Correlation & Regression Analysis, Index Numbers & Time Series, Sampling Methods |
| 23BA204 | Corporate Accounting | Core | 4 | Company Accounts, Share Capital & Debentures, Redemption of Debentures, Final Accounts of Companies, Valuation of Goodwill & Shares, Amalgamation & Absorption |
| 23BA205 | Business Law | Core | 4 | Indian Contract Act 1872, Sale of Goods Act 1930, Consumer Protection Act 2019, Negotiable Instruments Act 1881, Partnership Act 1932, Company Law Overview |
| 23BA206 | Introduction to Python for Analytics | Core | 4 | Python Fundamentals, Data Types & Structures (Lists, Tuples, Dictionaries), Control Flow & Functions, File Handling, Introduction to NumPy & Pandas, Basic Data Manipulation |
Semester 3
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 23BA301 | Managerial Economics | Core | 4 | Demand and Supply Analysis, Elasticity Concepts, Production and Cost Analysis, Market Structures & Pricing Strategies, National Income Accounting, Business Cycles |
| 23BA302 | Cost Accounting | Core | 4 | Cost Concepts & Classification, Material & Labour Costing, Overhead Allocation & Absorption, Job & Batch Costing, Process Costing, Standard Costing & Variance Analysis |
| 23BA303 | Relational Database Management System (RDBMS) | Core | 4 | Database Concepts & Architecture, ER Modeling, Relational Algebra, SQL Commands (DDL, DML, DCL), Database Design & Normalization, Transactions & Concurrency Control |
| 23BA304 | Business Communication & Etiquette | Core | 4 | Principles of Communication, Verbal & Non-Verbal Communication, Business Correspondence & Reports, Presentation Skills, Interpersonal & Cross-Cultural Communication, Professional Etiquette |
| 23BA305 | Python for Data Science Lab | Lab | 2 | Python Programming for Data, Data Loading & Cleaning (Pandas), Data Transformation & Aggregation, Basic Data Visualization (Matplotlib, Seaborn), Exploratory Data Analysis, Statistical Analysis with SciPy |
| 23BAO301 | Open Elective - I | Elective | 3 | Subject selected from a basket of open electives offered by the college. |
Semester 4
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 23BA401 | Financial Management | Core | 4 | Financial Decisions & Goals, Working Capital Management, Capital Budgeting Techniques, Cost of Capital, Leverage Analysis, Dividend Policy |
| 23BA402 | Operations Research for Business | Core | 4 | Linear Programming, Transportation Problems, Assignment Problems, Network Analysis (PERT/CPM), Queuing Theory, Decision Theory under Uncertainty |
| 23BA403 | Advanced Excel for Business Analytics | Core | 4 | Advanced Formulas & Functions, Data Validation & Conditional Formatting, Pivot Tables & Charts, Data Analysis Tools (Solver, Goal Seek), Power Query & Power Pivot, Dashboard Creation |
| 23BA404 | SQL for Data Analytics Lab | Lab | 2 | Advanced SQL Queries, Stored Procedures & Functions, Triggers & Views, Database Normalization Practice, Data Manipulation Language (DML), SQL Performance Tuning |
| 23BA405 | Marketing Analytics | Core | 4 | Marketing Metrics & KPIs, Customer Segmentation, Product & Pricing Analytics, Campaign Performance Measurement, Web & Social Media Analytics, Forecasting Marketing Trends |
| 23BAO401 | Open Elective - II | Elective | 3 | Subject selected from a basket of open electives offered by the college. |
Semester 5
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 23BA501 | Management Information Systems | Core | 4 | MIS Concepts & Components, Information Systems Development, Database Management Systems, Decision Support Systems (DSS), Enterprise Systems (ERP, SCM, CRM), E-business & M-commerce |
| 23BA502 | Research Methodology | Core | 4 | Research Design & Types, Data Collection Methods, Sampling Techniques, Hypothesis Testing, Data Analysis & Interpretation, Report Writing & Ethics |
| 23BA503 | Machine Learning for Business | Core | 4 | Introduction to Machine Learning, Supervised Learning (Regression, Classification), Unsupervised Learning (Clustering), Model Evaluation & Selection, Ensemble Methods, Introduction to Deep Learning |
| 23BA504 | Data Visualization with Tableau/Power BI | Core | 4 | Data Visualization Principles, Tableau/Power BI Interface, Connecting to Data Sources, Chart Types & Dashboards, Creating Interactive Reports, Storytelling with Data |
| 23BAE501 | Elective - I: Financial Analytics | Elective | 4 | Financial Ratios & Metrics, Portfolio Analysis, Risk Management & Modeling, Predictive Analytics in Finance, Valuation Techniques, Algorithmic Trading Basics |
| 23BAE502 | Elective - II: HR Analytics | Elective | 4 | HR Metrics & Dashboards, Workforce Planning Analytics, Recruitment & Retention Analytics, Performance & Engagement Analytics, Compensation & Benefits Analysis, Predictive HR Models |
Semester 6
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 23BA601 | Big Data Analytics | Core | 4 | Big Data Concepts & Characteristics, Hadoop Ecosystem (HDFS, MapReduce), Apache Spark, NoSQL Databases (Cassandra, MongoDB), Cloud-based Big Data Solutions, Stream Processing |
| 23BA602 | Econometrics for Business | Core | 4 | Econometric Models Introduction, Simple & Multiple Regression, Violation of Assumptions, Time Series Econometrics, Panel Data Analysis, Forecasting Models |
| 23BA603 | Project Work / Internship | Project | 8 | Problem Identification & Formulation, Data Collection & Pre-processing, Model Development & Implementation, Results Interpretation & Analysis, Report Writing & Documentation, Presentation & Defense |
| 23BAE601 | Elective - III: Operations Analytics | Elective | 4 | Supply Chain Analytics, Inventory Management & Optimization, Quality Control & Process Improvement, Logistics & Network Optimization, Forecasting in Operations, Simulation & Decision Modeling |
| 23BAE602 | Elective - IV: Retail Analytics | Elective | 4 | Retail Industry Metrics, Customer Segmentation & Loyalty, Sales & Merchandising Analytics, Inventory & Supply Chain in Retail, Store Performance & Location Analytics, E-commerce & Digital Retail Analytics |
