Analytics, BS

Analytics is an increasingly important skillset utilized in a wide range of occupations and more frequently in Analyst specific positions, and is projected to increase faster than the average growth rate across all occupations from 2018 to 2028.

Employers seeking analytics professionals with “moderate” levels of data analysis skills - typically positions at the bachelor’s level – most often prefer candidates with Analytics as a field of study. Skills frequently required in candidates are data analysis and the ability to interpret and communicate data analysis results to others, problem solving, mastery of spreadsheets, analysis tools, statistical software, relational databases as well as programming language. The general demand for Teamwork/Collaboration and Project Management reflects the need for employers to find analytics professionals with general business skills which can be used in a variety of function areas.

The Bachelor of Science in Analytics (BSA) helps to meet the demand from employers with an undergraduate program and entry level education requirements that prepares learners as data analyst practitioners capable of applying data analysis methods, technological, professional, and strategic expertise necessary for supporting decision making in organizations. With emphasis on experiential learning, the program provides dynamic opportunities for learners with varying degrees of work experience to practice their knowledge both globally and collaboratively while implementing effective data analysis concepts to real-life company demands.

The BSA has general foundation courses (including mathematical and philosophical logic), specific data analysis foundation courses, major required courses (such as Introduction to Analytics, Predictive Analytics, Introduction to Programming, Data Visualization and Communication, Data Warehousing, SQL and Data Mining), as well as a variety of elective courses on diverse domain areas.

Graduates of the BSA will have the opportunity to demonstrate their range and depth of skill to

  • Investigate theories, tools, and approaches in data analytics to identify and communicate data-driven insights for informed decision-making.
  • Articulate and defend the significance and implications of the work in data analytics in terms of challenges and trends in a local, national or global context.

  • Complete a project that requires the application of the principles, tools and methods of analytics to a comprehensive real-world problem.

  • Apply the principles, tools and methods of analytics to a project within a sponsoring organization to assist with the extraction, development, delivery, and/or translation/implementation of data analysis for tactical and/or strategic decision-making.

Complete all courses listed below unless otherwise indicated. Also complete any corequisite labs, recitations, clinicals, or tools courses where specified and complete any additional courses needed beyond specific college and major requirements to satisfy graduation credit requirements.

University-Wide Requirements

All undergraduate students are required to complete the University-Wide Requirements.

NUpath Requirements

All undergraduate students are required to complete the NUpath Requirements.

Foundation Courses

57 semester hours required

Complete the following:
ENG 1105
and ENG 1106
College Writing 1
and Lab for ENG 1105
ENG 1107
and ENG 1108
College Writing 2
and Lab for ENG 1107
ENG 3107
and ENG 3108
Writing for the Professions: Business and the Social Sciences
and Lab for ENG 3107
Complete one of the following:3
Writing to Inform and Persuade
Writing for the Web
CMN 1100Organizational Communication3
CMN 2310Professional Speaking3
PHL 2120Ethical Issues in Communication3
PHL 2310Symbolic Logic3
MTH 1100College Algebra3
MTH 2400Technology and Applications of Discrete Mathematics3
Information Technology
ITC 1100Human-Computer Interaction3
ITC 2000Principles of Systems Analysis and Design3
ITC 2016End-User Data Analysis Tools3
LDR 1200Assessing Your Leadership Capacity3
LDR 3400Evidence-Based Leadership and Decision Making3
Computer Engineering Technology
CET 2200Data Structures and Algorithms3
ALY 2010Probability Theory and Introductory Statistics3
ALY 2100Introduction to Programming for Data Analytics3

 Major Required Courses

27 semester hours required

Information Technology
ITC 2300Database Management Systems3
ITC 3300Structured Query Language (SQL)3
ITC 3320Data Warehousing Technologies3
ALY 3015Intermediate Statistics for Data Analytics3
ALY 3110Big Data and Web Mining3
ALY 3040Data Mining3
ALY 3070Communication and Visualization for Data Analytics3
ALY 4000Analytics using R3
ALY 4020Predictive Analytics Using R and Python3

Professional Electives

Complete 12 semester hours in the following subject areas below:12
Suggested Electives:
MGT 1100Introduction to Business3
MGT 2210Information within the Enterprise3
MKT 2100Principles of Marketing3
HRM 2320Human Resources Management3
ACC 2100Financial Accounting3
PJM 1100Project Management Fundamentals - Project Initiation and Close3


3 semester hours required

ALY 4850Analytics Capstone3


Complete a minimum of 21 semester hours to reach 120 semester hours. Courses from the major may not double count for Electives.

Suggested elective courses:
ART 2100Foundation in Visual Communication3
LDR 3400Evidence-Based Leadership and Decision Making3
ECN 1200Principles of Macroeconomics3
ITC 2020Digital Collaboration and Team Building3
ITC 2430E-Commerce Systems3
HRM 2320Human Resources Management3
ENG 3260Writing to Inform and Persuade3
TCC 3450Writing for the Web3
LDR 3200Leading and Managing Change3
BIO 1050Medical Terminology3
FIN 2105Introduction to Corporate Finance3
FIN 3310Financial Institutions and Markets3