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
Plan of Study Grid
Freshman
Semester 1Credits
ENGL 101
English Composition I
or English Composition I for English as a Second Language Students
4-6
MATH 164 Pre-Calculus for Business Students 3-4
General Education Tier I Course 3
General Education Tier I Course 3
INTD 101 Orientation to College *first time freshmen only 1
 Credits14-17
Semester 2
ENGL 102
English Composition II
or English Composition 2 ESL
4-6
MGMT 211 Principles of Management 3
General Education Tier I Course 3
General Education Tier I Course 3
Elective 3
 Credits16-18
Sophomore
Semester 1
MGMT 241 Global Business 3
ECON 207 Principles of Economics:Macro 3
MGMT 225 Business Enterprise Applications 3
ACCT 251 Financial Accounting 3
General Education Tier II Course 3
 Credits15
Semester 2
FINC 250 Financial Literacy: Strategies for Financial Success 3
ECON 208 Principles of Economics:Micro 3
ECON 203 Business Statistics 3
ACCT 252 Management Accounting 3
General Education Tier II Course 3
 Credits15
Junior
Semester 1
MGMT 251 Operations and Project Management Fundamentals 3
MGMT 235 Business Law I: Legal Environment of Business 3
FINC 305 Introduction to Data Science 3
FINC 405 Programming Basics for Business Analytics and Data Science 3
General Education Tier III Course 3
 Credits15
Semester 2
MKTG 231 Principles of Marketing 3
FINC 371 Managerial Finance 3
FINC 306 Statistical and Mathematical Foundations for Business Analytics and Data Science 3
FINC 430 Principles of Machine Learning 3
Major Elective or Minor Requirement 3
 Credits15
Senior
Semester 1
FINC 410 Introduction to Forecasting Models and Experimental Design for Business Analytics and Data Science 3
FINC 403 Fundamentals of Data Visualization for Business Analytics and Data Sciences 3
FINC 415 Basics of Data Collection, Data Warehousing, and Data Cleansing 3
Major Elective or Minor Requirement 3
Major Elective or Minor Requirement 2
 Credits14
Semester 2
FINC 495 Capstone in Data Science 3
MGMT 411 Business Policy 3
Major Elective or Minor Requirement 3
Major Elective or Minor Requirement 3
Major Elective or Minor Requirement 3
 Credits15
 Total Credits119-124

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.