BS in Business Analytics

4 Years On Campus Bachelors Program

Northern Arizona University

Program Overview

Northern Arizona University’s Bachelor of Science in Business Analytics combines business knowledge with technical training to help students turn complex data into meaningful insights for better decision-making. Designed for students interested in business, technology, and data-driven problem-solving, the program develops skills in Python programming, database management, statistical analysis, data visualization, and business intelligence, while allowing students to complete a business certificate or select additional business electives.

Curriculum Structure

The degree requires 120 units, including business analytics coursework, university requirements, and a certificate or business electives. The following is a suggested four-year progression based on NAU’s 2026–2027 progression plan; the exact course sequence may vary.

Year 1 – Building Business and Mathematical Foundations

Students begin by developing their understanding of business information systems, mathematics, economics, and academic communication. Courses such as Introduction to Computer Information Systems, Introduction to Business Statistics, and Finite Mathematics with Calculus help students build the technical and quantitative foundation needed for business analytics.

Year 2 – Developing Programming and Financial Skills

The second year introduces students to programming and core business concepts, helping them understand how data supports organizational decisions. Through Foundations of Business Programming, Python Programming for Business Analytics, and Financial Accounting for Business, students begin working with programming concepts, business data, and financial information.

Year 3 – Applying Analytics to Business Decisions

Students strengthen their analytical abilities through courses focused on business intelligence, management systems, and data visualization. Subjects such as Management Information Systems, Descriptive Analytics, Visualization and Decision Modeling for Business Analytics, and Applied Business Intelligence help students organize information, identify patterns, and communicate useful business insights.

Year 4 – Advanced Analytics and Professional Application

The final year focuses on advanced data management, specialized analytics, and practical application through a senior capstone. Courses such as Data Warehousing for Business Analytics, Marketing Analytics, and Data and Text Mining for Business Analytics allow students to explore predictive techniques, data-driven marketing, and business intelligence before completing their capstone experience.

Focus Areas

Business analytics, data visualization, Python programming, business intelligence, database management, data warehousing, statistical analysis, predictive analytics, marketing analytics, data mining, financial analysis, business decision-making, ethical data use.

Learning Outcomes

Students learn to collect, prepare, structure, and analyze business data using analytics and database tools, apply statistical and predictive methods to support decisions, create meaningful visualizations, communicate analytical findings through reports and presentations, and evaluate business problems using critical and ethical reasoning.

Professional Alignment and Accreditation

The program is STEM-designated and offered through the W. A. Franke College of Business. The university identifies ACBSP accreditation for its business programs, including Business Analytics, providing an external framework for business education quality and continuous improvement.

Reputation and Employability

NAU emphasizes practical analytics training through programming, data visualization, business intelligence, and applied projects. The official program information identifies potential career paths such as Business Analyst, Business Operations Analyst, Data Scientist, Financial Analyst, and Market Research Analyst. A verified program-specific employment rate or salary figure is not stated in the official information reviewed.

Experiential Learning (Research, Projects, Internships etc.)

Students gain practical experience by working with business-related datasets, learning analytics tools, and applying statistical and programming techniques to real business questions. The program emphasizes project work, decision-making simulations, data visualization, and the communication of findings, helping students build the technical and professional skills needed to support data-driven organizations.

Students can develop hands-on experience through the following opportunities:

Python Programming: Students learn to use Python for business data preparation, analysis, and visualization.
Analytics Software: Microsoft Excel, Tableau, RapidMiner, and Power BI are identified by NAU as tools used in the program.
Database Tools: SQL, Power Query, and dimensional modeling techniques support data acquisition, organization, and analysis.
Data Visualization: Students create visual representations of business information to communicate findings clearly.
Predictive Analytics: Students explore regression, machine learning, and other predictive methods to support business decisions.
Business Intelligence Projects: Applied Business Intelligence introduces students to data mining, predictive modeling, reporting, and decision-making.
Real-World Business Problems: Students work with varied datasets and apply analytical concepts to business challenges and organizational decisions.
Senior Capstone: The Business Analytics Capstone Experience brings together students’ analytical knowledge and communication skills in a final project.
Business Certificate: Students complete an undergraduate certificate offered through the W. A. Franke College of Business or select approved business electives, allowing them to develop additional areas of interest.

Progression & Future Opportunities

Graduates can pursue careers that combine business strategy, data analysis, technology, and decision-making. The program prepares students to work with business information, identify patterns, communicate insights, and support organizations in improving their operations and performance.

Potential career paths:

Business Analyst, Business Operations Analyst, Data Scientist, Financial Analyst, Market Research Analyst, Business Intelligence Analyst, Data Analytics Specialist, Marketing Analyst, Data Visualization Analyst, Predictive Analytics Analyst, Business Intelligence Consultant, Data Management Analyst.

Career development and graduate opportunities:

Career Services: NAU offers university career development resources to support students with career planning, professional preparation, and employment searches.
Employment and Salary Statistics: NA — verified program-specific employment rates and salary figures are not stated in the official program information reviewed.
Practical Business Experience: Students apply analytical techniques to business problems through projects, datasets, simulations, and the senior capstone.
Technical Skills: Experience with Python, Excel, Tableau, RapidMiner, Power BI, and SQL supports preparation for analytics-related professional roles.
Professional Recognition: The STEM designation identifies the degree as a science, technology, engineering, and mathematics program. ACBSP accreditation provides an external business education quality framework.
Graduation Outcomes: Graduates are expected to demonstrate analytical problem-solving, data preparation, statistical reasoning, visualization, professional communication, and ethical decision-making.

Further Academic Progression: Graduates may continue their education through postgraduate programs such as a Master of Science in Business Analytics, Data Science, Information Systems, Applied Statistics, or an MBA with a business analytics focus, depending on their academic interests and the admission requirements of the chosen institution.