Business Analytics and Data Science, B.S.

The Bachelor of Science in Business Analytics and Data Science program will prepare students with the skills needed to gather, store, analyze and interpret large amounts of data in order to make business decisions.  The program is designed to cater to the burgeoning need for analytics and data science professionals in various industries such as finance, marketing, retail and accounting.

The business analytics and data science bachelor’s program at NJCU reflects the university’s commitment to empower a diverse, underserved population and be an institution of higher education nimble in its response to dynamic 21st Century opportunities and challenges.  The program also underscores the resolve of the NJCU School of Business to be a data-driven institution.  

The program will be fully geared towards practice.  Students learning experiences will be grounded in real world contexts.  Students will learn analytical skills and use software tools that are currently popular in the industry, to find solutions to business data analysis problems that are commonly encountered in practice.  Students will also learn the ethical responsibilities of working with large amounts of data, which in many cases could be private.  Graduates of the program will be thoroughly prepared to take on the role of a data scientist in the industry. 

The program will also prepare students to take the Certified Analytics Professional (CAP) certification.

Incoming students may transfer up to 50% of the School of Business courses required in the major, pending department evaluation for transfer equivalency. Once matriculated at NJCU, transfer students must complete at least 30 credits at NJCU to satisfy the university’s residency requirement. Students must also maintain a GPA of 2.5 or better in courses taken in the School of Business. Students must earn a grade of C or higher in each School of Business course (ACCT, BUSI, ECON, FINC, MGMT, MKTG) used in fulfillment of a graduation requirement.

Common Core Requirements (33 credits)
MGMT 225Business Enterprise Applications3
MGMT 251Operations and Project Management Fundamentals3
ECON 203Business Statistics3
MGMT 211Principles of Management3
MKTG 231Principles of Marketing3
MGMT 241Global Business3
ACCT 251Financial Accounting3
ACCT 252Management Accounting (Pre-Requisite ACCT 251)3
MGMT 235Business Law I: Legal Environment of Business3
FINC 371Managerial Finance (Pre-Requisite ECON 208, ACCT 252, MATH 164)3
MGMT 411Business Policy (Pre-Requisite FINC 371)3
Specialization Requirements (24 credits)
FINC 305Introduction to Data Science3
FINC 306Statistical and Mathematical Foundations for Business Analytics and Data Science3
FINC 405Programming Basics for Business Analytics and Data Science3
FINC 415Basics of Data Collection, Data Warehousing, and Data Cleansing3
FINC 410Introduction to Forecasting Models and Experimental Design for Business Analytics and Data Science3
FINC 403Fundamentals of Data Visualization for Business Analytics and Data Sciences3
FINC 430Principles of Machine Learning3
FINC 495Capstone in Data Science3
Electives (18 credits)
Students may take electives as approved by the Department Advisor in general business, or across disciplines including but not limited to courses from Economics, Finance, Accounting, Marketing, Computer Science, Political Science, GeoScience, or group classes for a Minor or Specialization.
General Education Courses Required
MATH 164Pre-Calculus for Business Students4
or ECON 221 Analytics For Business and Economics
ECON 207Principles of Economics:Macro3
ECON 208Principles of Economics:Micro3

Student Learning Outcomes

Upon completion of the Bachelor of Science in Business Analytics and Data Science, students will be able to:

  1. Identify ethical issues and understand the implications of social responsibility for sustainable business practices.
  2. Evaluate information and apply critical thinking skills to identify solutions and inform business decisions.
  3. Utilize technology, apply quantitative methods and interpret data to solve business problems.
  4. Integrate knowledge of core business concepts and collaborate productively as part of a team.
  5. Work effectively in a diverse environment and understand how global and cultural issues effect the organization and its stakeholders.
  6. Compose clear and concise forms of written communication to effectively convey ideas and information associated with business topics.
  7. Communicate business concepts effectively through oral presentation.
  8. Create large databases by effectively gathering, storing and cleansing large amounts of data from a diverse array of sources ranging from real-time financial market data to social media data.
  9. Apply statistical analysis and machine learning techniques to build predictive models.
  10. Explain the findings of the data analysis using visualization techniques.
  11. Demonstrate ability to use large and diverse datasets and apply predictive analytics in making business decisions and effectively disseminating results.