The Milgard School of Business MSBA degree integrates STEM (Science, Technology, Engineering, Mathematics) perspective into business education and analysis.
Milgard's MSBA is a diligently designed work-compatible applied master's degree. The MSBA delivers a sophisticated curriculum that will develop the next generation of savvy business analysts, project managers, analytics managers, chief analytics officers, digital talents and T-shaped analytical thinkers.
The MSBA features unique, hands-on business analytics through the center's digital transformation lab. From the first day of the program, students will join a team to tackle real-world analytics projects with companies. Students have the opportunity to apply concepts, principles and methods associated with business analytics to solve complex problems in an application domain associated with their area of interest (e.g. marketing analytics, HR analytics, sports analytics, supply-chain logistics analytics, sales analytics and more). Students meet with industry advisors and mentors.
Use the latest technology to deliver a world-class experience. As part of the MSBA program, students will learn to use these industry recommended software solutions.
Hands-on Applied Learning - From the first day of the program, students will join a team to tackle real-world analytics projects with companies.
Focuses on foundations of evidence based management. Explains the concepts with innovative uses of information systems, data, information, knowledge and analytics to support managerial decision-making. Explores how to collect, store, manage and convert data to information, knowledge and actionable insights.
Gartner Research indicates that more than 50% of Business Analytics (BA) projects fail due to not following fundamental project management principles. Focuses on how organizations need to make analytics part of their organizational strategy, and how they can implement analytics projects successfully by following sound project management principles. It focuses on strategy definition, initiating, planning, executing, controlling and completing analytics projects in a variety of environments for sustainable competitive advantage.
Focuses on how organizations can evaluate, design and implement sound business process management practices, and integrate analytics into their business processes and workflows for maximum performance. The course will also cover Service Oriented Solutions (e.g. dynamic business processes, architectures and infrastructures), data and predictive model ownership issues, embedding analytics in business processes, alignment of business process management with corporate strategy.
Focuses on statistical foundations of decision making processes. Topics will include, but are not limited to: multiple linear regression, models for quantitative and qualitative predictors, building regression models, autocorrelation, non-linear regression, piecewise linear regression, inverse prediction, weighted least squares, ridge regression, robust regression and non-parametric regression.
Focuses on the skills and knowledge necessary for mastery of the use of quantitative modeling tools and techniques to support decision analysis. Some of the deterministic optimization techniques (e.g. linear, nonlinear, integer optimization, network models) and uncertain decision making techniques (e.g. decision trees, transportation models, queuing theory) are covered.
Focuses on some of the primary business data mining topics (descriptive, predictive and prescriptive) through advance analysis of applied, realistic datasets in areas like demand forecasting, credit scoring, customer relationship management, financial analysis, healthcare and supply chain management.
This course will cover the basic concepts, principles, and major algorithms in text mining. These will be used to discover interesting patterns, extract useful knowledge, and support decision making.
Focuses on some of the primary concepts, methods, tools and solutions to develop a social media strategy, and to collect, process and transform social media data into information processes, knowledge, actionable decisions and processes. It also covers how organizations make use of social media as a strategy to gain a competitive advantage.
Evaluate the concepts with innovative uses of cognitive solutions to either solve existing business problems or create new business opportunities, and improve the performance of organizations. Analyze how to utilize cognitive tools, assistants, collaborators and coaches effectively.
Focuses on how to apply the concepts, methods and solutions associated with data, analytics, smart machines and digital solutions to real opportunities in an application domain. Topics will include, but are not limited to: analysis of organization and market demand, business model development, opportunity analysis for digital transformation.
Focuses on processes performed to analyze and plan digital transformation and innovation to a wide variety of opportunities and challenges. Topics will include, but are not limited to: requirements gartering, defining scope, risk analysis, detailed transformation and technology planning.
Focuses on processes performed to design and develop data and digital solutions to a wide variety of opportunities and challenges. Topics will include, but are not limited to: collection, storage, analysis of data and development of digital solutions.
Focuses on processes performed to prototype data and digital solutions to a wide variety of opportunities and challenges. Topics will include, but are not limited to: develop, prototype and lessons learned, analyze findings, recognize ethical dilemmas and social responsibilities.
The special topics offerings provide MSBA students the opportunity to explore a variety of academic subjects based on the current interests and teaching expertise and scholarly research of faculty. The size and structure of the class will vary according to the subject offered and the instructor. Topic will vary. Content to be announced in advance of scheduled offerings.
Provides an opportunity to work independently exploring specific data and business analytics topics in greater depth. The student must develop a research proposal and make arrangements with a faculty member to supervise the project prior to course registration. Permission of faculty is required.
Provides students with practical knowledge and experience in a private or public work environment. Gives students opportunities to develop a strategic plan under faculty guidance, and to perform field work utilizing the skills developed in the classroom. Permission of faculty is required.