Main Content
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The Milgard School of Business MSBA degree integrates STEM perspectives 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.
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The MSBA features unique, hands-on business analytics through the Center for Business Analytics Innovation 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. Look at our students' past work - Pro-bono Business Analytics Consulting.
Key features:
- 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.
- Experience the best of both worlds—quarterly on-campus sessions ensure networking opportunities while online classes give you the flexibility you need
- Interact with your peers through web conferencing, discussion boards and social media
- Weekly synchronous office hours via video teleconferencing
- Learn to lead and collaborate with teams in virtual environments
- Receive regular contact from Milgard’s faculty
- Participate in online and face-to-face workshops and coaching sessions
All cohorts will have:
- A total of 40 credits in graduate coursework
- Face-to-face Saturday classes + eLearning (40% in-person + 60% asynchronous eLearning)
- Class meetings at UW Tacoma on Saturdays (9:00am - 12:20pm and 1:30pm - 4:50pm) with synchronous office hours via video teleconferencing
Program: Face-to-face Saturday classes + eLearning (40% in-person + 60% asynchronous eLearning)
Program location: UW Tacoma with synchronous office hours via video teleconferencing
Class day/times: Saturdays, 9:00am - 12:20pm and 1:30pm - 4:50pm
Program duration: 12 months = 4 quarters (summer, autumn, winter, spring)
Total credits: 40
Class Type: Cohort-based
Course Sequence: Lock-step
Curriculum
Curriculum for accelerated work-compatible 12-month program
The Milgard School of Business MSBA degree is 40 credits of graduate courses over the course of 12-months (accelerated full-time program).
Tentative schedule: Order of courses may need to be changed to provide the best student learning experience
|
|
SUMMER (A and B) |
AUTUMN |
WINTER |
SPRING |
|
Business Data Analytics Information |
TBANLT 520 Analytics Strategy & Big Data Management (4 credits) (Summer A) |
TBANLT 510 Business Analytics (4 credits) |
TBANLT 550 Analytical Decision Making (4 credits) |
TBANLT 570 Text Mining (4 credits) |
|
TBANLT 530 Business Process & Workflow Analysis (4 credits) (Summer B) |
TBANLT 540 Applied Regression Models (4 credits) |
TBANLT 560 Data Mining (4 credits) |
Electives: TBANLT 5XX Emerging Analytics (4 credits) |
|
|
Knowledge Wisdom Practice Outcome |
TBANLT 591 Applied Project: Digital Transformation Lab I (2 credits) |
TBANLT 592 Applied Project: Digital Transformation Lab II (2 credits) |
TBANLT 593 Applied Project: Digital Transformation Lab III (2 credits) |
TBANLT 594 Applied Project: Digital Transformation Lab IV (2 credits) |
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Projects
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. Look at our students' past work - Pro-bono Business Analytics Consulting.
Summary of Courses
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Course Number |
Course Title |
Credits |
|
TBANLT 510 |
Business AnalyticsFocuses 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.
|
4 |
|
TBANLT 520 |
Analytics Strategy and Big Data ManagementGartner 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.
|
4 |
|
TBANLT 530 |
Business Process and Workflow AnalysisFocuses 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.
|
4 |
|
TBANLT 540 |
Applied Regression ModelsFocuses 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.
|
4 |
|
TBANLT 550 |
Analytical Decision MakingFocuses 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.
|
4 |
|
TBANLT 560 |
Data MiningFocuses 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.
|
4 |
|
TBANLT 570 |
Text MiningThis 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.
|
4 |
| Emerging Analytics |
(Adaptive/TBD per Year) - one of the following elective courses Focuses on the latest trends regarding evolving processes or specializations within the business analytics field. This is chosen as a new topic each year and fulfills the elective requirement for the MSBA program. |
|
|
TBANLT 580 |
Social Media AnalyticsFocuses 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. |
4 |
|
TBANLT 585 |
Cognitive Analytics /Artificial IntelligenceEvaluate 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. |
4 |
| TBANLT 590 |
Special Topics: Advance Regression for Data ScienceThis class will explore advanced regression techniques for data analysis. This can include generalized linear models, multilevel modeling, structural equation modeling, CART analysis, and advanced forecasting models. It will include applications of these techniques, and knowing how to pick the right analysis for which data. |
4 |
|
|
Total Credits |
32 |
|
TBANLT 591 |
Applied Project: Digital Transformation Lab IFocuses 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.
|
2 |
|
TBANLT 592 |
Applied Project: Digital Transformation Lab IIFocuses 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.
|
2 |
|
TBANLT 593 |
Applied Project: Digital Transformation Lab IIIFocuses 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.
|
2 |
|
TBANLT 594 |
Applied Project: Digital Transformation Lab IVFocuses 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.
|
2 |
|
|
Total Credits |
8 |
|
TBANLT 590 |
Special Topics in Business AnalyticsThe 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.
|
2-4 max. 4 |
|
TBANLT 600 |
Independent Study or ResearchProvides 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.
|
2-4 max. 4 |
|
TBANLT 601 |
InternshipProvides 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.
|
2-4 max. |
