Master of Science in Business Analytics

Program Description

The Master of Science in Business Analytics program is designed to equip students with the skills and knowledge necessary to analyze and interpret complex data sets for making informed business decisions, while effectively communicating those insights to diverse stakeholders. It will equip students with a comprehensive skill set for navigating the dynamic intersection of business and data analytics. Through a rigorous curriculum, hands-on projects, and real-world applications, students will develop the expertise needed to harness the power of data in driving strategic business decisions. The impact of artificial intelligence (AI) on business efficiencies and effectiveness will be examined, and predictive analysis will be used to uncover patterns, forecast trends, ensure data security. This program encompasses the key areas of statistical analysis, programming proficiency, database management, data visualization, machine learning, business intelligence, and ethical considerations.

Coursework in this program provides a foundation for select industry certifications. These certifications enhance employment opportunities but are not a state specific requirement.

Program Outcomes

Upon completion of this program, the student should be able to:

Combine appropriate statistical methods and exploratory data analysis (EDA) techniques based on diverse business datasets to extract meaningful and actionable insights.
Use high level programming languages (such as SQL, Python, and R) to facilitate data-driven business solutions.
Design an appropriate database for cleansing, storing, and retrieving data efficiently based on business specifications.
Build artificial intelligence (AI) and machine learning algorithms and predictive modeling techniques to solve business problems.
Create business intelligence visualizations and reports to communicate analytical findings to diverse stakeholders and to contribute to informed decision-making.
Develop data governance policies and standards that incorporate ethical considerations, legal implications, and privacy challenges associated with data collection and usage.

Program Content

A minimum of 34.00 semester credit hours is required for graduation.

Required Courses

All courses, 34.00 semester credit hours, are required.

BU 509 - Statistics for Business Decision-Making Semester Credit Hours: 4.00
BU 511 - Times Series Analysis Semester Credit Hours: 3.00
BU 512 - Data Management for Analysis Semester Credit Hours: 3.00
BU 513 - Machine Learning Semester Credit Hours: 3.00
BU 514 - Text Analytics and NLP Semester Credit Hours: 3.00
BU 676 - Responsible Business Analytics Semester Credit Hours: 3.00
BU 677 - Sector Analytics Semester Credit Hours: 3.00
BU 678 - Communicating with Data Visualization Semester Credit Hours: 3.00
BU 679 - Advanced Applications in Business Analytics Semester Credit Hours: 3.00
BU 683 - Foundations of Business Analytics for Leaders Semester Credit Hours: 3.00
BU 696 - MSBA Capstone Semester Credit Hours: 3.00
Or
BU 698 - MSBA Internship Semester Credit Hours: 3.00

Distribution of Contact Hours by Course

Distribution of Contact Hours by Course
Course Number	Lecture Hours	Internship Hours	Total Contact Hours	Credits
BU 509	60.00	0.00	60.00	4.00
BU 511	45.00	0.00	45.00	3.00
BU 512	45.00	0.00	45.00	3.00
BU 513	45.00	0.00	45.00	3.00
BU 514	45.00	0.00	45.00	3.00
BU 676	45.00	0.00	45.00	3.00
BU 677	45.00	0.00	45.00	3.00
BU 678	45.00	0.00	45.00	3.00
BU 679	45.00	0.00	45.00	3.00
BU 683	45.00	0.00	45.00	3.00
BU 696 (or BU 698*)	45.00	0.00	45.00	3.00
Totals with Capstone	510.00	0.00	510.00	34.00
*Totals with Internship BU 698 MSBA Internship: Contact Hours: 0/0/135/135	465.00	135.00	600.00	34.00