Master of Business Analytics
The MS in Business Analytics prepares graduates for successful careers working with data across a wide range of organizations. Students build a strong foundation at the intersection of business, statistics, and computing. In addition to a firm grounding in analytical techniques and applications, students gain the ability to effectively communicate and use the results of data analytics for innovative solutions to catalyze business growth. Graduates are deeply engaged with the private and public sector, acquiring relevant skills to provide immediate value to employers.
The School of Business Administration at the University of Montana will help meet a growing workforce need with its new master’s degree in business analytics.
The Master of Science degree, a joint effort between marketing and management information systems, combines new elements with several existing programs at UM. The core curriculum includes the study of business intelligence, big data analysis, business statistics, statistical computing, data mining and management, and communicating insights based on data analysis and associated decision-making. MSBA graduates will understand the fundamentals of statistics and programming with a strong foundation in business. They will be poised for successful careers working with data across multiple disciplines.
Demand for data analytics in the U.S. has skyrocketed in recent years. In 2013 alone, demand shot up 67 percent nationally, with local and regional employers also seeking graduates with data analytics experience.
“The MSBA is very innovative and designed to deliver critical knowledge and skills for the technology intensive business environment of today. It serves a rapidly growing need in the marketplace and it is likely to attract enrollment from both Montana business professionals, who need to hone their business analytics skills, and from out-of-state and international students.” -Dr. Simona Stan, MBA Director
The Masters of Business Analytics (MSBA) is a 32 credit, one year program, offered on campus at the University of Montana. Upon completion of the program foundation classes, the one year MSBA consists of 17 credits of required courses and 15 credits of electives to assist in self-designing a program to meet your individualized needs.
Foundations
BMIS 326 - Introduction to Data Analytics. This course introduces the terminology and application of big data and data analytics. Students will complete cases in a variety of disciplines as they become acquainted with some of the software, tools, and techniques of data analytics.
STAT 451 – Statistical Methods I. Intended primarily for non-mathematics majors who will be analyzing data. Graphical and numerical summaries of data, elementary sampling, designing experiments, probability as a model for random phenomena and as a tool for making statistical inferences, random variables, basic ideas of inference and hypothesis testing.
BMKT 560 – Marketing & Stats. (can also be taken as Stats 216 - Introduction to Statistics and BMKT 325 - Marketing Principles) Introduction to marketing principles that create long-term competitive advantage for an organization. Topics include environmental analysis, marketing planning, segmentation analysis, target marketing, and planning for product, price, promotion and distribution. Business statistics covered including t-tests, analysis of variance, regression and correlation analysis; statistics applications in context of marketing research and marketing problems.
Internship or work experience
Required Courses (15 credits)
BMIS 601 – Business Intelligence. This course intends to provide graduate students with the foundational knowledge necessary to transform big data into useful business intelligence. The course will provide students with the skills, tools, and techniques required to collect, synthesize, and distribute information to support intelligent decision-making at the managerial level.
BMKT 670 - Applied Data Analytics. This course applies statistical skills and technical expertise to real-world big-data business applications. Students will work with the tools of data science and hone their ability to answer business questions through the analysis of data.
BMKT 642 - Advanced Marketing Research. The purpose of the course is to learn how to provide information for better business decision making. Students study the different aspects of marketing research as it relates to business problems and develop a mindset that continually relies on information-based decisions.
BMIS 625 – Text Mining of Unstructured Data. An integration of data science theory and the actual practice of searching, sorting, relating, and deriving results from textual data. Students will be exposed to machine learning, natural language processing, as well as other computer assisted data mining techniques and then gain hands-on proficiency in the practice of data science using the software from data mining and document analysis vendors.
BMIS 650 – Quantitative Analysis. Quantitative methods supporting managerial decision-making. Theory and logic underlying such methods as linear programming and simulation. Solution of complex problems and practice of interpersonal skills in team projects.
BMKT 680 - Big Data and Innovation. The course provides an integrative, capstone experience for students to reflect on and apply the data science tools they have learned in the Master of Business Analytics program. In addition, this course will focus on the innovation and creativity aspects of big data, or how big data can unleash new insights and innovations that solve customer and societal problems. The course will train future managers to think strategically and innovatively—about data, about opportunity, about value. It will ensure that students are proficient in strategy, customer value and insights. Students engage in a capstone professional paper/project.
Electives (17 Credits)
Electives are not limited to courses provided below
BMKT 420 – Integrated Online Marketing. Exploration and application of marketing communications principles to the internet environment. Students develop individual WordPress websites/blogs, learn about online marketing techniques, and complete online marketing and social media projects.
CSCI 444 – Data Visualization. Visualization fundamentals and applications using special visualization software; formulation of 3-D empirical models; translation of 3-D models into graphical displays; time sequences and pseudo-animation; interactive versus presentation techniques; special techniques for video, CD and other media.
CSCI 564 – Applications of Mining Big Data. Introduction to existing data mining software systems and their use, with focus on practical exercises. Topics include data acquisition, data cleansing, feature selection, and data analysis. Credit not allowed for both CSCI 464 and CSCI 564.
JRNL 414 - Investigations. Introduction to methods and ethics of investigative reporting, emphasizing computer-assisted research and analysis of public records and databases.
MART 500 – Digital Tech in the Arts I. This course explores the relationship between aesthetics and the emerging capabilities of digital technology. It will cover the historical relationship between science and art up to the end of the 20th century and examine the methodology of critical artistic applications.
BMIS 575 - Introduction to Consulting. Managerial approach to consulting engagements. Includes scoping and writing proposals, presenting to clients, documenting consulting work, and interpersonal skills necessary for successful consulting. Course does not require a technical background.
BMIS 674 - Mgmt of Information Systems. The tactical/operational responsibilities and roles of the CIO. Includes governance issues, supporting the learning organization, managing the technologies, and managing the development of systems. Focuses on management; does not require a technical background.
"Leading the charge toward smarter, data-driven marketing strategies is the University of Montana. There is a vast difference between demand for marketing analytics and the supply of well-trained analysts, as well as marketing professionals who can draw insights from data..." - Taylor Radey, PR 20/20
