Welcome to 10 months of business analytics immersion. In the MS in Business Analytics program, you’ll combine strong technical and quantitative training and building comprehensive business acumen. You’ll do it with the direction of some of the greatest minds in business: Goizueta professors. In a collaborative, project-driven learning environment, you’ll create innovative solutions to business problems for real-world clients. By the end of the program, you’ll see a data problem from every angle and find innovative solutions.
STEM-Credentialed Program
Fast-Tracked Learning
MS in Business Analytic Program Timeline
Explore the highlights of what 10 months in our MS in Business Analytics program look like. We combine market-relevant skills, experiential learning, and professional development to create business data scientist ready to tackle any data-driven problem.
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Summer Semester
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Fall Semester
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Fall Semester
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Spring Semester
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Spring Semester
Capstone Project
Apply the skills you learned in your coursework and solve sponsored firms’ business problems, using proprietary data. This is your chance to put your skills to the test tackling a real problem for a real client using real data.Capstone Project -
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Course Map by Semester
MS IN BUSINESS ANALYTICS COURSES
This course examines how statistical methods lead to understanding and describing data. We use R/RStudio to review basic data exploration and statistical methods. Topics covered include simple descriptive statistics through hypothesis testing and modeling.
In this course, students gain competence in practical database, data warehousing, and data management skills with emphasis on query, data modeling, ETL, and data management. They will also become familiar with major elements of the big data ecosystem.
Learn modern network analysis methods and how to apply them to network data. Study the latest in theory, methods, and substantive applications. This course covers the application of network theory to the study of careers, competition, innovation, inequality/stratification, IT-mediated networks, network formation, and network dynamics.
This is an introduction to basic concepts in machine learning, both supervised and unsupervised. The basic ideas of neural networks will be presented. Machine learning from data streams (online learning) using stochastic gradient descent is also covered.
Where the art of graphic design meets with the science of data analytics. Learn how to perform exploratory analysis through visualization, how to create professional-looking visualizations for use in business reports and presentations, and how to design interactive visualizations and dashboards.
Delve into a number of selected current and emerging data analytics areas that are increasingly important for organizations. Areas include advanced elements of the predictive modeling process, ensemble methods, cost-aware data analytics, mining text and data, recommender systems, and other advanced topics.
This course introduces students to optimization and simulation, powerful techniques for better decision-making (in particular, linear, integer and non-linear programming), and Monte Carlo and discrete event simulation, and discuss their application to problems in business and data analytics.
The MSBA Capstone Course leverages skills and techniques learned throughout the course of the program and applies them to real-world business situations. Students formally define problems, clean data, aggregate with other data sources, and identify and use appropriate analytical techniques to address questions.
This course uses analytic methods to solve marketing problems (including pricing, customer relationship management and sales forecasting). We emphasize the development of tools that can be implemented in practice to support decision making and rely on frequentist and Bayesian methodologies.
This course focuses on tools and techniques applicable to decision making in sports. The analytical foundations for the class are classical statistical and optimization techniques. We solve sports problems using tools such as linear regression, logistic regression, Markov chains, and optimization.
This course introduces students to statistical and computational methods used in employee recruitment, selection, promotion and turnover. A significant portion of the course is devoted to experimental methods designed to test the efficacy of HR policies before an organization implements them.
Goizueta Experts
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Leading the Conversation Ramnath Chellappa
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Tackling Big Tech Vilma Todri
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Exploring How Tech Changes Us Panos Adamopoulos
Start with a Solid Foundation
You want to be ready to lead at the critical nexus where business, data, and technology intersect. With our STEM-credentialed, multidisciplinary curriculum, you can. So what is it about Goizueta that separates us from the rest? Start with the fact that you will be taught by business school faculty with deep academic knowledge and extraordinary industry experience. Pair that with a small, intimate learning community where you will be guided by both academic and industry mentors.
Real Data. Real Clients. Real World.
MS Business Analytics Capstone Projects
Learn by doing. That’s the philosophy that drives our MS in Business Analytics program. You’ll work within a small team mentored by faculty to apply everything you learned in the program to devise a data-driven solution for a real client business problem. Projects conclude with an industry day where you’ll present the analysis and findings of your work to the firms that have shared their data.
Gaining Confidence to Implement Change
Sherrie Liu 18MSBA
Originally from China, Sherrie Liu earned her undergraduate degree in the U.S., majoring in marketing and minoring in art history. After working for a little more than two years at Unilever in customer development, she decided to earn an MS in Business Analytics from Emory to help her focus on "looking at the numbers and really trying to figure out what was going on in the business."