Master's Programs

Featured Faculty

Suri Weisfeld-Spolter, Ph.D.
Associate Professor of Marketing Professor Suri Weisfeld Spolter

”I always find out about my students' backgrounds and work experiences so I can relate to them. I want them to feel comfortable enough to ask questions and share their opinions. Most important, I want them to feel confident in their abilities to succeed. It is my goal to make class interesting, practical, enjoyable, and motivating.”

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M.B.A. in Business Intelligence / Analytics


Information is the lifeblood of every company, as is the ability to identify, gather, extract, and analyze this raw data. Business intelligence uses a variety of software applications to transform these facts and figures into useful information that can then be used as a catalyst for constructive decision making, cutting costs, improving operations, and identifying new business opportunities. With an M.B.A. in Business Intelligence / Analytics, you will make an immediate and valuable contribution to any company, with exceptional proficiency in the science of business modeling, database systems, data warehousing, data mining, and benchmarking.


  • M.B.A. core courses offered weeknights, alternating weekends or during the day on the main campus, alternating weekends at select other campuses and online. The Business Intelligence / Analytics courses are offered online or weeknights at our main campus.
  • Program can be completed in as little as 21 months.
  • Program begins four times annually with starts in October, January, April, and July.
  • Program offered in conjunction with NSU's Graduate School of Computer and Information Sciences
  • A Business Intelligence / Analytics Certificate is also available.

Total Credits: 39

M.B.A. Core Courses (21 total credits)

Business Intelligence / Analytics Concentration Courses
(18 total credits)
QNT 5470 Data Analytics for Management  
MMIS 630 Database Management and Applications   
MMIS 642 Data Warehousing  
MMIS 643 Data Mining  
MMIS 692 Capstone Project in Business Intelligence  
QNT 5495 Advanced Data Analytics for Management  

Current students: Please consult your Academic Advisor for program requirements or access SharkLink for your CAPP report. Program requirements are subject to change, and your Academic Advisor or CAPP report can provide you with the courses required for your catalog term.

Full-Time professionals are available to discuss the M.B.A. in Business Intelligence / Analytics curriculum with you in greater detail. Simply call 800.672.7223 Ext. 25168 or contact our Enrollment Services Staff.

QNT 5470     Data Analytics for Business Management  (3 cr.)

This course provides an overview of data analytics in business management and the technologies that can be used to enhance data-driven decision making. The course introduces data analytics frameworks and best practices for integrating data analytics into organizational business processes to be used to improve competitiveness, profitability, growth or operational efficiency. Students also gain experience with software tools used for data preparation, analysis, and reporting. Prerequisite: QNT 5160 or QNT 5040.

MMIS 630   Database Management and Applications  (3 cr.)

The application of database concepts to management information systems. Design objectives, methods, costs, and benefits associated with the use of a database management system. Tools and techniques for the management of large amounts of data. Database design, performance, and administration. File organization and access methods. The architectures of database systems, data models for database systems (network, hierarchical, relational, and object-oriented model), client-server database applications, distributed databases, and object-oriented databases.

MMIS 642   Data Warehousing  (3 cr.)

This course includes the various factors involved in developing data warehouses and data marts: planning, design, implementation, and evaluation; review of vendor data warehouse products; cases involving contemporary implementations in business, government, and industry; techniques for maximizing effectiveness through OLAP and data mining. Prerequisite: MMIS 630 Database Systems.

MMIS 643   Data Mining  (3 cr.)

This course emphasizes the fundamental concepts and techniques of data mining. Concepts will be illustrated with case studies of real data mining examples. The focus is to find knowledge from huge amounts of data being handled electronically. Students will gain hands on experience using data mining tools on real data. Necessary background concepts in statistics and programming will be provided. Prerequisites: MMIS 671 Decision Support Systems or QNT 5040 Business Modeling, and MMIS 630 Database Systems.

MMIS 692   Capstone Project in Business Intelligence  (3 cr.)

This capstone project requires students to employ the knowledge and skills assimilated in the four courses to design and develop a business intelligence application that leads to direct and measurable value for the students� organization. Prerequisites: MMIS 630 Database Systems, MMIS 642 Data Warehousing, and MMIS 643 Data Mining.

QNT 5495     Advanced Data Analytics for Business Management  (3 cr.)

This course integrates knowledge of data management, data mining techniques, predictive modeling, and business process models. Students will apply advanced data analytics techniques to real-world business problems and create and evaluate data-driven solutions to uncover new business strategies and improve organizational competitiveness. The effectiveness of data-analysis techniques and knowledge discovery methods in business applications is also discussed. Prerequisites: QNT 5470, MMIS 0630, MMIS 0642, MMIS 0643, and MMIS 0692.

Foundation Course Descriptions

QNTP 5000     Foundations of Business Statistics  (3 cr.)

This course covers collection, description, analysis, interpretation, and presentation of data to support business decision making. Probability distributions, central limit theorem, statistical inference for uni-variate data; correlation analysis and introduction to linear regression modeling and their application to real world business problems are discussed. The data analysis capabilities of Microsoft Excel are integrated throughout the course.

FINP 5001     Accounting and Finance Foundations  (3 cr.)

A survey of the essentials topics in accounting and finance includes modern corporate environments, agency and governance, accounting principles, financial statements, ratio analysis, time value of money, financial decision making tools.