Overview
The Bachelor of Commerce (Data Analytics & Business Intelligence) program prepares students to transform business data into meaningful insights and strategic decisions. The program uniquely integrates core commerce disciplines — accounting, finance, taxation and management — with industry-relevant data analytics and business intelligence skills such as Excel financial modelling, SQL, Python programming and Power BI dashboarding.
A key strength of the program is its alignment with the Institute of Analytics (IoA). Through this association, students gain exposure to globally recognised analytics standards, industry frameworks and professional best practices, enhancing both academic depth and career readiness. The IoA integration strengthens students’ professional credibility and supports their transition into analytics-driven roles across industries.
Learning is driven by hands-on labs, case studies, real-world datasets and project-based assessments, ensuring graduates are not only technically proficient but also ethically and professionally responsible, with strong grounding in data governance, privacy and compliance. On completion, students are well equipped to add immediate value to analytics, finance, business intelligence and operations teams.
What You’ll Learn
- Extract, clean and model structured and semi-structured data using SQL and Python.
- Design interactive dashboards and data stories with Power BI to support operational decisions.
- Apply statistical analysis and machine learning (regression, classification, clustering) for forecasting, segmentation and insights.
- Build Excel-based business models that link analytics outcomes to financial and managerial metrics.
- Evaluate data solutions for fairness, bias, privacy and security to ensure compliance.
- Communicate findings clearly through visualizations, executive summaries and presentations.
- Plan and execute capstone analytics projects or internships demonstrating measurable business impact.
Practical Skills
- Commerce foundation: Financial Accounting, Corporate Accounting, Financial Management and Taxation.
- Analytics fundamentals: Applied Business Statistics, Database Systems (SQL) and Python Programming for Analytics.
- Visualization & BI: Data Visualization with Power BI and Data Storytelling & Dashboards.
- Advanced analytics: Machine Learning with Python and Advanced Analytics with Python.
- Specialized electives: Options like HR Analytics, Retail Analytics, Consumer Analytics or Healthcare Analytics.
- Tools & ethics: Business Modelling with Excel, Data Governance, Digital Commerce and Security.
- Capstone & placement: Business research and report writing plus a mandatory final-semester internship or project.
- Internship: The final semester is fully devoted to internships and capstone projects with partner organizations in analytics, consulting, fintech, retail, healthcare and other sectors. Students work on live data challenges — from building ETL pipelines and dashboards to developing KPI frameworks and production-ready models — applying classroom knowledge to real business problems.
Career Pathways
- Data Analyst / Business Intelligence Analyst
- Financial Analytics Associate
- SQL/BI Developer (Power BI/Tableau)
- Machine Learning Engineer / Predictive Modelling Analyst
- Analytics Consultant / Reporting Analyst
- HR / Retail / Consumer Analytics Specialist
- Risk & Compliance Analytics Specialist
Programme Education Objectives
| PEOs | Programme Educational Objectives |
|---|---|
| PEO1 | To provide graduates with a broad, industry-relevant foundation in accounting, finance, taxation, costing, banking, marketing and business operations, together with industry-aligned competencies in statistics, database management, programming for analytics (Python/SQL), business intelligence tools and accounting analytics, enabling them to perform effectively in entry-level commerce, finance and analytics roles across industry, services and public practice, and to pursue professional or entrepreneurial pathways. |
| PEO2 | To embed understanding of data governance, privacy, cybersecurity, ethical AI/ML usage and regulatory obligations to ensure responsible analytical practice. |
| PEO3 | To develop advanced statistical, machine learning and modelling capabilities, enabling graduates to derive insight from structured and semi-structured data for evidence-based decision-making. |
| PEO4 | To cultivate data storytelling, dashboard design, stakeholder communication and collaborative problem-solving for translating analytics into actionable business strategies. |
| PEO5 | To foster project execution capability, capstone development, internships and continuous upskilling in cloud data platforms, scalable Business Intelligence pipelines and emerging analytics technologies. |
Programme Outcomes (POs)
| POs | Programme Outcomes |
|---|---|
| PO1 | Apply core principles of accounting, finance, taxation, costing, marketing and business operations to prepare, interpret and validate business records and reports, and apply business intelligence and analytics techniques to prepare, validate and interpret organisational dashboards and operational reports. |
| PO2 | Analyse and model structured and semi-structured datasets using statistical, machine-learning and programming tools to produce predictive and prescriptive insights. |
| PO3 | Create and present visual narratives, dashboards and data stories that communicate analytical findings to technical and non-technical stakeholders. |
| PO4 | Evaluate analytics solutions for fairness, privacy, security and regulatory compliance and apply ethical principles in AI/ML implementations. |
| PO5 | Design, develop and deploy analytics projects or capstone solutions using cloud platforms, Business Intelligence pipelines and collaborative industry engagement. |
Programme Structure
B.Com – Data Analytics and Business Intelligence
| Semester I | Semester II | Semester III | Semester IV | Semester V | Semester VI |
|---|---|---|---|---|---|
| Language I (Kannada: Saahitya Sourabha - I / Hindi: Gadya Varidhi / Additional English: Translations selected from South India) | Language I (Kannada: Saahitya Sourabha - II / Hindi: Gadya Kalash/ Additional English: Translations selected from East and North East India) | Language I (Kannada: Saahitya Dhaare - I / Hindi: Kavya Sudha/ Additional English: Translations selected from Central and West India) | Language I (Kannada: Saahitya Dhaare - II / Hindi: Khand Kavya-Shabari/ Additional English: Translations selected from North India) | Income Tax - II | Advanced Management Accounting or Retail Analytics |
| Language II (Generic English: Readings from Literature and Language Skills) | Language II (Generic English: Interpretations of Literature and Language Skills) | Language II (Generic English: Perceptions of Literature and Language Skills) | Language II (Generic English: Insights from Literature and Language Skills) | Goods and Services Tax | |
| Financial Accounting - I | Financial Accounting - II | Corporate Accounting | Business Law & Ethical Practices | Advanced Analytics with Python | |
| Corporate Administration | Business Mathematics | Data Visulaization with Power BI | Machine Learning with Python | Management Accounting | Investment Management & Portfolio Management or Consumer Analytics |
| Business Modelling with Excel | DBMS with SQL | Python Programming for Analytics | Financial Management | Costing Methods and Techniques or HR Analytics | |
| Applied Business Statistics | Entrepreneurship & Startup Management | Digital Transformation in Business or Market Analysis & Business Decision | Essentials of Business Analytics or Digital Commerce & Security | Advanced Financial Management or Health care Analytics | |
| Constitution & Moral Values - I | Environmental Studies | Business Communication | Information Visualization and Cognitive Principles | Business Research & Report Writing | |
| - | - | Constitution & Moral Values - II | - | - |
Eligibility Criteria
Candidates who have completed two-years pre-university programme of Karnataka State or its equivalent of any state or country are eligible for admission into this programme.
- Pass in 10 + 2 in formal commerce schooling with 50% and above will be eligible for BCom (Data Analytics and Business Intelligence - IOA Certification) programme.
