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Bachelor of Business Administration in Data Science

The Bachelor of Business Administration (BBA) in Data Science is a forward-thinking undergraduate programme crafted to develop the next generation of business leaders who can think analytically, act strategically, and lead through data. This unique three-year course seamlessly integrates core business principles with cutting-edge data science tools and techniques—preparing students to make intelligent, data-driven decisions in a rapidly evolving digital economy.

Blending the disciplines of business management and technology, the program trains students to extract meaning from complex data sets, interpret insights through visualization, and apply them to solve real-world business challenges. Students gain practical knowledge in areas such as business intelligence, statistical analysis, machine learning, artificial intelligence, Python, R, SQL, data mining, and cloud computing—all within the context of business functions like finance, marketing, operations, and human resources.

The curriculum is designed to be immersive and experiential, featuring a balanced mix of classroom instruction, hands-on labs, live industry projects, case studies, internships, and capstone research. Students develop proficiency in industry-standard tools such as Tableau, Power BI, and Excel, while also exploring the ethical implications of data usage and the transformative impact of big data on global business models.

By graduation, students are not only equipped with robust technical and analytical capabilities but also possess a deep understanding of how to translate data into business value—making them highly sought-after professionals in roles spanning business analytics, consulting, marketing intelligence, financial analytics, and beyond.

Programme Duration

3 years

Programme type

Full time

Programme Structure 2025

STE – BBA Data Science

Eligibility Criteria

Candidates should have passed PUC/12th standard or equivalent from any stream.

Key Features

After completion of the programme, a student will be able to:
  • Apply the principles of psychology in multidisciplinary domains to achieve personal, professional, and organisational outcomes
  • Design, implement, and critically validate well-being programmes in counselling and industrial settings
  • Produce meaningful and relevant research studies addressing psychosocial issues in counselling, clinical, and industrial settings
  • Solve professional, ethical, and multicultural issues in diverse professional and organisational settings

Scope and Objectives

Scope:
India is rapidly emerging as a global hub for data analytics, with the proliferation of digital services, government-led digitization initiatives (such as Digital India), and the exponential growth of sectors like e-commerce, fintech, healthcare, and IT. Organizations across both private and public sectors are leveraging data science to streamline operations, personalize customer experiences, and drive innovation. Against this backdrop, the BBA in Data Science equips students with the dual advantage of managerial insight and analytical expertise—making them uniquely positioned to meet the growing demand for professionals who can bridge the gap between data and decision-making. The program offers significant career opportunities in business analytics, digital marketing, financial analytics, operations, and consulting. Additionally, with India’s vibrant startup ecosystem and focus on entrepreneurship, graduates are well-equipped to launch or support data-driven business ventures. The degree also serves as a strong foundation for pursuing MBA programs, PG diplomas, or professional certifications such as Data Analytics (NSDC), Google Data Analytics, and other AICTE-approved short-term courses.

Programme Structure

STE - BBA Data Science
  • Management Process
  • IT for Business
  • Financial Accounting
  • Business Economics
  • Business Economics with Kannada / Hindi

Programme Assessment

  • Choice-Based Credit System (CBCS): The university follows CBCS, which allows students to choose courses and earn credits based on their performance
  • Grades and GPA: Students are awarded grades for each course in a semester, and their Semester Grade Point Average (SGPA) is calculated to measure their academic performance. Cumulative Grade Point Average (CGPA) is used to evaluate the overall performance of a student across all semesters.
  • Prescribed Curriculum: Each program has a prescribed curriculum or Scheme of Teaching and Evaluation, which includes the required courses, laboratories, and other degree requirements. It also incorporates SWAYAM and Massive Open Online Courses (MOOCs) offered by reputed institutions.
  • Auditing Courses: Students have the option to audit courses, which allows them to gain additional exposure without the pressure of obtaining a grade. This can give them an advantage in placements.
  • Evaluation System: The evaluation of students is comprehensive and continuous throughout the semester. It consists of Continuous Internal Evaluation (CIE) and Semester End Examination (SEE). CIE and SEE carry equal weightage of 50% each, resulting in a total evaluation of 100 marks for each course, regardless of its credit value.
  • Assessment Methods: Before each semester, faculty members may choose assessment methods such as assignments, seminars, quizzes, group discussions, case studies, practical activities, class presentations, industry reports, etc., with suitable weightage for each.
  • Semester End Examination: A Semester End Examination is conducted for all registered courses at the end of each semester. However, some courses that already have Continuous Internal Evaluation may not require a SEE. 
  • Makeup Examinations: Students who fail the Semester End Examination in one or more courses are eligible for makeup examinations, which provide an opportunity to retake the failed exams and improve their grades.

Programme Outcome

Program Educational Objectives (PEOs)

  • PEO1: To provide a coherent understanding of how various industries in the manufacturing and service sector operate and are managed
  • PEO2: To build managerial, analytical and critical thinking skills for designing digital marketing strategies and analysis across industries,
  • PEO3: To address student’s unique learning needs and provide them them with the disciplinary knowledge and skills to apply in unfamiliar contexts, for start-ups or any entrepreneurial venture
  • PEO4: To imbibe knowledge, understanding and skills required to identify problems, collect relevant quantitative and qualitative data drawing on a wide range of sources, and use methodologies as appropriate to the subject(s) for formulating evidence-based solutions.
  • PEO5: To expose interpersonal and information technology skills to design ethical and sustainable business and marketing solutions to real-world problems.
  • PEO6: To build a solid foundation to pursue higher level studies and research in areas of marketing and business administration.

Program Outcomes (POs)

Graduates will be able to:
  • PEO1: Demonstrate a foundation of digital marketing theoretical concepts and practices through innovative techniques to step out as corporate ready professionals.
  • PEO2: Use capabilities and skills in areas of business and marketing to take up roles in digital marketing services for associate and analyst positions across diverse industries.
  • PEO3: Apply sensitivity towards organizational, economic and cultural diversity while designing solutions to meet global challenges
  • PEO4: Build creativity and innovative thinking to develop entrepreneurial skills.
  • PSO1: Apply foundational and advanced data science principles, including data cleaning, preprocessing, and statistical analysis, to solve complex business problems across industries such as marketing, finance, operations, and HR.
  • PSO2: Utilize data analytics tools, programming languages (e.g., Python, R), and machine learning algorithms to build predictive models and generate actionable insights for business decision-making.
  • PSO3: Demonstrate the ability to interpret large datasets, visualize trends, and present business intelligence using tools like Tableau, Power BI, and other data visualization platforms to inform strategic business decisions.
  • PSO4: Exhibit critical thinking and problem-solving skills to identify key business challenges, analyze data from various sources, and apply appropriate methodologies to formulate effective, data-driven solutions.
  • PSO5: Apply ethical considerations and data privacy principles in handling sensitive information, ensuring compliance with data protection regulations and promoting responsible data usage in business environments.
  • PSO6: Prepare for professional roles in data analytics, business intelligence, and data science fields, with readiness for both corporate positions and entrepreneurial ventures in data-driven industries such as tech, finance, and consulting.

Course Outcomes


STE - BBA Data Science
  • CO1: Understand core concepts of data science, business analytics, and statistical analysis in the context of business decision-making.
  • CO2: Apply data wrangling, cleaning, and preprocessing techniques to prepare datasets for analysis using tools like Excel, SQL, and Python.
  • CO3: Use data visualization techniques and tools such as Tableau and Power BI to present business insights in an impactful and meaningful manner.
  • CO4: Demonstrate the ability to build and evaluate predictive models using machine learning algorithms for business forecasting and classification tasks.
  • CO5: Analyze business scenarios and apply data analytics strategies to solve functional problems in marketing, finance, operations, and HR.
  • CO6: Interpret and communicate analytical results effectively to both business and technical audiences through written reports and visual dashboards.
  • CO7: Evaluate the ethical, legal, and social implications of data science practices, with a focus on data privacy, security, and responsible AI.
  • CO8: Collaborate in cross-functional teams to develop data-driven solutions through business case studies, real-time datasets, and industry-based projects.

What expertise will you gain?

Solid foundation in core business disciplines such as marketing, finance, operations, HR, and entrepreneurship.

Mastery of data collection, cleaning, processing, and interpretation techniques.

Proficiency in using tools such as Excel, SQL, Python, R, and Tableau/Power BI for data analysis and visualization.

Ability to interpret complex datasets and generate actionable business insights.

Knowledge of statistical techniques including regression, hypothesis testing, and inferential statistics.

Ability to build and apply predictive models using machine learning algorithms to forecast trends and behaviors.

Hands-on experience in coding (Python, R), querying databases (SQL), and handling large datasets.

Understanding of business intelligence systems and their role in digital transformation across sectors.

Strong communication, presentation, and storytelling skills using data.

Team collaboration, project management, and problem-solving abilities for cross-functional roles.

Exposure to real-world problems through capstone projects, internships, and interaction with industry mentors.

Readiness for roles such as Business Analyst, Data Analyst, Operations Analyst, Marketing Analyst, and more.

Career Opportunity

  • Business Analyst
  • Data Analyst
  • Marketing Analyst
  • Financial Analyst (with Data Focus)
  • Operations Analyst
  • Product/Data Associate in Tech Startups
  • Data-Driven Entrepreneur
  • CRM/Data Executive in Retail, FMCG, and BFSI

Placements at

CMR University

200+ Recruiters, Pre-Placement modules from first semester focus on employability, emphasis on experiential learning, extensive focus on Internships, Training for competitive examinations – CAT, GRE, TOEFL, CMAT, Bank PO, and more.

Testimonials

"I loved the infrastructure of CMR University and its management. As a club coordinator I learnt how to manage team and the events helped me to grow my confidence level. I would like to specially thank the placement cell for guiding me and providing me a good platform (company) for my career."

Radheshyam Thakur

BCA

"I loved the infrastructure of CMR University and its management. As a club coordinator I learnt how to manage team and the events helped me to grow my confidence level. I would like to specially thank the placement cell for guiding me and providing me a good platform (company) for my career."

Radheshyam Thakur

BCA

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FAQs

The BBA in Data Science is a 3-year undergraduate programme divided into 6 semesters. It integrates core business administration knowledge with analytical and technical skills required to leverage data for strategic decision-making in modern organizations.

While a traditional BBA focuses on management fundamentals, the BBA in Data Science incorporates data-centric subjects like data analytics, machine learning, statistical modelling, and business intelligence tools. This specialization enables students to make data-driven decisions and prepares them for careers at the intersection of business and technology.

Yes. In the later semesters, students can opt for electives to explore niche areas such as:

  • Machine Learning for Business

  • Business Intelligence and Visualization

  • Predictive Analytics

  • Data Engineering and Cloud Analytics

Big Data and AI Applications in Business

Graduates are well-prepared for a range of data-centric roles, including:

  • Business/Data Analyst

  • Data Science Associate

  • Financial Analyst (Data Focused)

  • Marketing Analyst

  • Risk Analyst

  • Product Analyst

  • Operations Analyst

  • AI/ML Assistant Roles

Data-Driven Entrepreneur

After completing BBA in Data Science, students can pursue:

  • MBA in Business Analytics / Data Science

  • MSc in Data Science, Business Analytics, or AI

  • PG Diploma in Data Engineering or Cloud Computing

Certifications like Google Data Analytics, Tableau, or Microsoft Power BI

You will gain:

  • Proficiency in tools like Excel, Python, SQL, Tableau, Power BI, and R

  • Foundational and advanced data analytics skills

  • Business problem-solving using data

  • Machine learning model development

  • Data storytelling and visualization

  • Critical thinking and decision-making with data

Ethical data usage and compliance awareness

Yes. The BBA in Data Science includes internships, capstone projects, and hands-on training with real-time datasets. This ensures practical exposure and industry-readiness.

Candidates must have passed 12th Grade / PUC or equivalent from any stream. While prior technical experience is not mandatory, an aptitude for analytics and interest in data-driven decision-making is recommended.

Yes. The university provides excellent placement support with 200+ recruiters across sectors. Specialized training in data tools, communication, interview preparation, and career readiness is part of the curriculum from the first semester.

Eligibility Check: Ensure you’ve completed 12th/PUC or equivalent in any stream.
 Application: Fill out the online application on the university’s admissions portal.
 Selection: Based on document verification, entrance exam (CMRUAT if applicable), and personal interview.
 Offer Letter & Enrollment: Successful candidates receive an offer letter and proceed with the enrollment process, including fee submission.

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