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.
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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.
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Complete a project that requires the application of the principles, tools and methods of analytics to a comprehensive real-world problem.
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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
| Code | Title | Hours |
|---|---|---|
| English | ||
| Complete the following: | ||
| ENG 1105 and ENG 1106 | College Writing 1 and Lab for ENG 1105 | 4 |
| ENG 1107 and ENG 1108 | College Writing 2 and Lab for ENG 1107 | 4 |
| ENG 3107 and ENG 3108 | Writing for the Professions: Business and the Social Sciences and Lab for ENG 3107 | 4 |
| Complete one of the following: | 3 | |
| Writing to Inform and Persuade | ||
| Writing for the Web | ||
| Communication | ||
| CMN 1100 | Organizational Communication | 3 |
| CMN 2310 | Professional Speaking | 3 |
| Philosophy | ||
| PHL 2120 | Ethical Issues in Communication | 3 |
| PHL 2310 | Symbolic Logic | 3 |
| Mathematics | ||
| MTH 1100 | College Algebra | 3 |
| MTH 2400 | Technology and Applications of Discrete Mathematics | 3 |
| Information Technology | ||
| ITC 1100 | Human-Computer Interaction | 3 |
| ITC 2000 | Principles of Systems Analysis and Design | 3 |
| ITC 2016 | End-User Data Analysis Tools | 3 |
| Leadership | ||
| LDR 1200 | Assessing Your Leadership Capacity | 3 |
| LDR 3400 | Evidence-Based Leadership and Decision Making | 3 |
| Computer Engineering Technology | ||
| CET 2200 | Data Structures and Algorithms | 3 |
| Analytics | ||
| ALY 2010 | Probability Theory and Introductory Statistics | 3 |
| ALY 2100 | Introduction to Programming for Data Analytics | 3 |
Major Required Courses
27 semester hours required
| Code | Title | Hours |
|---|---|---|
| Information Technology | ||
| ITC 2300 | Database Management Systems | 3 |
| ITC 3300 | Structured Query Language (SQL) | 3 |
| ITC 3320 | Data Warehousing Technologies | 3 |
| Analytics | ||
| ALY 3015 | Intermediate Statistics for Data Analytics | 3 |
| ALY 3110 | Big Data and Web Mining | 3 |
| ALY 3040 | Data Mining | 3 |
| ALY 3070 | Communication and Visualization for Data Analytics | 3 |
| ALY 4000 | Analytics Using R | 3 |
| ALY 4020 | Predictive Analytics Using R and Python | 3 |
Professional Electives
| Code | Title | Hours |
|---|---|---|
| Complete 12 semester hours in the following subject areas below: | 12 | |
MGT, MKT, FIN, PJM, HMG, CET, LDR, BTC | ||
| Suggested Electives: | ||
| MGT 1100 | Introduction to Business | 3 |
| MGT 2210 | Information within the Enterprise | 3 |
| MKT 2100 | Principles of Marketing | 3 |
| HRM 2320 | Human Resources Management | 3 |
| ACC 2100 | Financial Accounting | 3 |
| PJM 1100 | Project Management Fundamentals - Project Initiation and Close | 3 |
Capstone
3 semester hours required
| Code | Title | Hours |
|---|---|---|
| ALY 4850 | Analytics Capstone | 3 |
Electives
Complete a minimum of 21 semester hours to reach 120 semester hours. Courses from the major may not double count for Electives.
| Code | Title | Hours |
|---|---|---|
| Suggested elective courses: | ||
| ART 2100 | Foundation in Visual Communication | 3 |
| LDR 3400 | Evidence-Based Leadership and Decision Making | 3 |
| ECN 1200 | Principles of Macroeconomics | 3 |
| ITC 2020 | Digital Collaboration and Team Building | 3 |
| ITC 2430 | E-Commerce Systems | 3 |
| HRM 2320 | Human Resources Management | 3 |
| ENG 3260 | Writing to Inform and Persuade | 3 |
| TCC 3450 | Writing for the Web | 3 |
| LDR 3200 | Leading and Managing Change | 3 |
| BIO 1050 | Medical Terminology | 3 |
| FIN 2105 | Introduction to Corporate Finance | 3 |
| FIN 3310 | Financial Institutions and Markets | 3 |