Bachelor of Science in Business Intelligence and Data Science

4 Years On Campus Bachelors Program

Indiana University Bloomington

Program Overview

The B.S. in Business Intelligence and Data Science is designed for students who want to combine business knowledge with advanced analytical and computational skills, with 120 credits covering business, data science, mathematics and statistics, plus electives and experiential learning. Students develop expertise in areas such as Python, machine learning, data mining, databases, big data analytics, and business analytics while learning how to translate complex data into practical business decisions.

Curriculum Structure

Year 1: Students build their foundations in business communication, mathematics, computing and statistics through courses such as BUS-X 101 GenAI 101, MATH-M 211 Calculus, and CSCI-C 200 Intro to Computers and Programming. They then strengthen their communication and quantitative reasoning through BUS-C 204 Business Writing, CSCI-C 241 Discrete Structures for Computer Science, and STAT-S 350 Introduction to Statistical Inference.

Year 2: The curriculum moves into the intersection of technology and business with BUS-K 303 Technology & Business Analysis, CSCI-A 310 Problem Solving Using Data, and BUS-L 395 Introduction to Law, Ethics and Governance of Business Digital Environment. Students also develop deeper technical and quantitative capabilities through CSCI-B 351 Intro to AI, MATH-E 201 Linear Algebra for Data Science, and financial analysis coursework.

Year 3: Students advance into sophisticated analytical and business applications through BUS-K 353 Business Analytics and Modeling, DSCI-D 351 Big Data Analytics, and BUS-G 350 Business Econometrics. Courses such as BUS-K 327 Modeling Business Data (Excel) and CSCI-B 365 Intro to Data Analysis and Mining further develop their ability to model, analyze, and interpret business data.

Year 4: The final year emphasizes strategic application, with BUS-G 492 Predictive Analytics for Business Strategy providing a direct connection between analytics and business decision-making. Students use their remaining business and computational electives to develop a more specialized profile aligned with interests such as fintech analytics, supply chain analytics, visualization, or advanced AI.

Focus areas

Business intelligence, data science, business analytics, artificial intelligence, machine learning, big data analytics, data mining, database technologies, predictive analytics, financial analytics, supply chain analytics, data visualization, quantitative business decision-making.

Learning outcomes

Students develop the ability to use quantitative methods, computing, statistics, data analysis and business knowledge to identify complex problems, work with large datasets, build analytical models, interpret findings, and communicate data-driven recommendations that support organizational decision-making.

Professional alignment (accreditation)

The B.S. in Business Intelligence and Data Science is STEM-designated and jointly delivered by Kelley and Luddy. The official programme information identifies the degree as a selective, rigorous four-year STEM program; no separate programme-specific professional accreditation is stated on the official programme pages reviewed.

Reputation (employability rankings)

Kelley’s Bloomington undergraduate business program is ranked #6 overall in the U.S. News & World Report Best Undergraduate Business Programs 2027 rankings, with eight specialty areas ranked in the national top 10. Kelley also reports more than 141,000 alumni, while its undergraduate career services reports that 96% of actively seeking Kelley graduates from the 2024–25 graduating group were employed or accepted into graduate school within three months.

Experiential Learning (Research, Projects, Internships etc.)

The program is structured around applying quantitative and computational skills to real business problems rather than treating data science as purely theoretical. Students work with programming, AI, data analysis, data mining, big data, databases and Excel-based business modelling, while the program also provides access to the facilities and broader learning environments of both Kelley and Luddy. The curriculum specifically includes 25+ credits of electives and experiential learning, allowing students to explore areas such as fintech analytics, supply chain analytics, visualization and advanced AI.

Students can build practical experience through:

Programming and computational tools: CSCI-C 200 Intro to Computers and Programming, CSCI-B 351 Intro to AI, and computational electives develop programming and computational problem-solving skills.
Data analytics: CSCI-A 310 Problem Solving Using Data, DSCI-D 351 Big Data Analytics, and CSCI-B 365 Intro to Data Analysis and Mining provide hands-on exposure to working with and interpreting data.
Business modelling: BUS-K 353 Business Analytics and Modeling and BUS-K 327 Modeling Business Data (Excel) connect analytical techniques directly with business decision-making.
Predictive analytics: BUS-G 492 Predictive Analytics for Business Strategy allows students to apply analytical methods to strategic business problems.
Luddy Hall: Students have access to Luddy Hall, a 124,000-square-foot facility featuring makerspaces, classrooms, advising and career services, and teaching and research spaces.
Luddy makerspaces: Luddy's makerspace network supports hands-on collaboration and includes digital fabrication equipment, electronics resources, 3D printers, laser cutters and hardware/software platforms.
Career and employer engagement: Kelley Undergraduate Career Services provides job-search coaching, career exploration and interview strategy, while more than 2,500 companies recruited Kelley students for internships and full-time positions.
Industry exposure: Kelley’s recruiting network includes employers such as Deloitte, JPMorgan Chase, Morgan Stanley, Amazon, Oracle, Salesforce, Accenture, Cummins, Gartner, Goldman Sachs, and PwC.
Study abroad: Kelley reports that more than 60% of its Bloomington students study abroad through short-term, semester and summer programs across multiple countries and continents.

Progression & Future Opportunities

Graduates of the B.S. in Business Intelligence and Data Science can pursue roles that combine analytical, computational and business expertise, including business intelligence analyst, data scientist/machine learning engineer, financial quantitative analyst, product or growth analyst, analytics consultant, and risk analyst. The programme is designed around the ability to interpret data and translate analytical findings into actions, giving graduates potential applications across technology, finance, consulting and other data-intensive industries.

Typical career opportunities include: Business Intelligence Analyst, Data Scientist/Machine Learning Engineer, Financial Quantitative Analyst, Product or Growth Analyst

Career services: Kelley Undergraduate Career Services provides personalized career guidance, job-search coaching, career exploration and interview preparation, alongside employer connections and campus recruiting opportunities.
Employment outcomes: Kelley reports that 96% of actively seeking graduates in its 2024–25 undergraduate cohort reported full-time employment or graduate-school acceptance within three months. This is a Kelley-wide figure rather than a BIDS-specific outcome, since the BIDS program is a new degree.
Salary information: Kelley reports an overall average starting salary of $78,780 for Kelley Bloomington graduates; this is a Kelley-wide figure and should not be interpreted as a BIDS-specific salary.
Employer network: Kelley reports more than 2,500 companies recruiting its students for internships and full-time positions. Named recruiting employers include Deloitte, JPMorgan Chase, Morgan Stanley, Amazon, Oracle, Salesforce, Accenture and PwC.
Industry engagement: Employers including Kodiak Solutions and Deloitte have specifically described the value of combining data analytics capabilities with business knowledge, and Kelley identifies the BIDS curriculum as responding to employer demand for professionals who can interpret data and use it to solve business problems.
Graduation outcomes: Because BIDS began with its inaugural class in 2025 and its initial graduates are expected in 2030, programme-specific graduate employment statistics are not yet available.
Long-term value: The degree's STEM designation and interdisciplinary preparation across business, statistics, computing and data science can support careers where analytical and technical skills are combined with business decision-making.

Further Academic Progression: After completing the B.S., students can continue into graduate study in areas such as business analytics, data science, information systems, finance or management. IU offers graduate pathways including Kelley’s M.S. in Business Analytics and M.S. in Information Systems, as well as Luddy’s M.S. in Data Science, which offers tracks including Applied Data Science, Big Data Systems, Computational and Analytical, and Managerial Data Science.