Master of Science in Business Analytics Curriculum

The Wake Forest University School of Business’ Master of Science in Business Analytics (MSBA) curriculum is relevant for today’s workforce, crafted with input from corporate partners to meet industry demands. Yet, because Big Data and the skills needed to draw insights from it continue to evolve, our MSBA curriculum also looks toward the future. Course content and projects shed light on the field’s real-world applications, illustrating where the technical knowledge gained intersects with business acumen. Our graduates then become key professionals for identifying patterns, predicting trends, and shaping business decisions, no matter the industry where they secure a position.

Goals of the MSBA Curriculum

The Wake Forest School of Business grounds our on-campus MSBA curriculum in applied statistics, management science, and business domain knowledge. We then weave in team-based projects throughout to amplify and identify real world–based applications for the concepts taught in the classroom. 

Big picture, the 10-month MSBA program trains students on the full spectrum of analytics methodologies and highlights all the ways organizations currently apply data-driven applications. Throughout this intensive, immersive curriculum, you’ll:

  • acquire essential programming skills, including R, SAS, Tableau, and SQL;
  • learn to apply analytics across key business disciplines, including finance, marketing, operations, and human resources;
  • be able to supplement your coursework with presentations from visiting speakers and thought leaders;
  • hone advanced quantitative capabilities and technical skills, and discover all the areas where they intersect with traditional business concepts;
  • understand responsible and ethical data usage practices;
  • utilize the Center for Analytics Impact (CAI) in the classroom and for team-based projects to analyze large datasets, master data mining and predictive modeling, and formulate actionable insights using real-time information from our corporate partners; and
  • leave with a marketable skill that’s essential for extracting insights, streamlining organizational efficiency, identifying new product lines, improving customer service, driving innovation, and making better business decisions.

In total, the MSBA curriculum extends over three semesters and requires 37 credit hours. All students begin in the summer semester and graduate by May of the following year.

“We assembled a group of highly accomplished analytics professionals to advise us as we sought to build a program connected to the marketplace. The result is a program that not only provides the necessary technical skills, but also focuses on business acumen and experiential learning through access to our unique corporate partnerships. With innovative courses like Analytics in the Boardroom and Analytics in Society, our MSBA program also leverages the strength of Wake Forest as a liberal arts university focused on educating the whole person.”

Jeffrey Camm
Associate Dean of Business Analytics and Inmar Presidential Chair of Business Analytics

Curriculum at a Glance

Anyone interested in this program needs to have earned an undergraduate degree prior to enrollment and have a solid background in calculus and statistics. Additionally, programming skills aren’t just an asset—they’re essential for the MSBA curriculum’s more technical courses. 

To get up to speed, we recommend attending the Summer Programming Bootcamp. This five-day, non-credit course held before the Summer semester offers a thorough introduction to key programming languages, and it’s recommended for all students who have no or limited programming knowledge. The course covers R and RStudio, reading and visualizing data in R, data types, functions and “if” statements, and loops. Learn more about who should take this class and what it entails.

Summer Semester

The five-week summer semester covers all foundational coursework needed to succeed within the Master of Science in Business Analytics program and encourages all students to start exploring related career interests and pathways. All participants need to display mastery of the foundational subjects before proceeding on to the rest of the curriculum.

Summer Module
Probability & Statistical Modeling
Analytics Software Technology
Career Management

Probability and Statistical Modeling (3.0 Credit Hours)

Learn to model uncertainty through probability, decision analysis, simple linear regression, multiple linear regression, and model selection and to assess the underlying assumptions of these mathematical models.

Analytics Software Technology (3.0 Credit Hours)

Become familiar with key data management and analytics software and programming languages. In the process, the course covers techniques for importing data, data manipulation, cleansing, transformation, creating new variables, and introductory data analysis.

Career Management (1.0 Credit Hour)

Explore where the MSBA program aligns with your career aspirations, the various directions data analytics knowledge can take you, and what you need to prepare for these next steps.

Fall Semester

Starting in late August, the Fall semester consists of a combination of semester-long courses and two mini modules that examine the relationship among data, business analytics, and organizational performance in greater depth.

Mini 1 Mini 2
Business Metrics Machine Learning
Data Analysis & Business Modeling Bus Analytics Practicum I:
Mess to Model
Visual Analytics and Influencing
Data Management
Predictive Analytics & Data Mining

Business Metrics (1.5 Credit Hours)

Because data analytics integrates with and improves operational processes, this course lays down a solid foundation in business topics, allowing students to see where technical skills and analytics methodologies fit into and enhance an organization’s strategy.

Data Analysis and Business Modeling (1.5 Credit Hours)

Course content takes your spreadsheet skills to the next level. Learn how to manage and analyze data and create business models with this key business tool through higher-level functions and analysis features. Additionally, understand what constitutes good modeling and how to audit business models.

Machine Learning (1.5 Credits)

Machine learning becomes essential for parsing and organizing large volumes of data, be it text, numbers, or images. This course gives you an understanding of the algorithms and statistical models on which machine learning is based and how this artificial intelligence–rooted technology draws out insights from and applies patterns to available data.

Practicum I: Mess to Model (1.5 Credit Hours)

Part of a three-course sequence for gaining real-world project-based experience, this class sees students grouped into teams, where they work under the direction of a faculty mentor and collaborate with a corporate partner. In the process, you’ll gain a hands-on understanding of problem scope, data requirements, expected deliverables, the analytics techniques needed to provide results, and leadership principles.

Visual Analytics and Influencing (3.0 Credit Hours)

Understand how to communicate your analyses to all levels of management through data visualizations, and learn key principles and techniques for transforming data points into an effective, convincing narrative.

Data Management (3.0 Credit Hours)

Coursework goes through database design and usage concepts. In the process, you’ll learn the latest methods for transforming large amounts of data and become familiar with data manipulation best practices. 

Predictive Analytics and Data Mining (3.0 Credit Hours)

Discover how to analyze datasets in greater detail and make predictions through linear and logistic regression, classification, decision trees, clustering, and text mining. While the course touches on theoretical concepts and practical computational skills, you’ll also have the opportunity to analyze and deliver results for real-time datasets.

Spring Semester

Beginning in early January, this semester is divided into two separate modules, during which students continue to develop models for forecasting, optimization, and yielding actionable intelligence and explore multi-industry applications of data analysis. Students also finish the three-course team-based practicum and present their findings.

Mini 3 Mini 4
Analytics in Society Digital Marketing Analytics
Process Analytics Prescriptive Analytics
Forecasting Financial & Risk Analytics
Marketing Analytics Supply Chain Analytics
Bus Analytics Practicum II:
Model to Insight
Business Analytics Practicum III:
Insight to Impact

 

Second Summer Term – Consulting Concentration

For those choosing to add a Consulting concentration to their MSBA degree experience, the program continues after the spring semester for a final summer semester. This concentration is designed for those students who wish to further enhance their consulting skills obtained in the standard MSBA program.

All four of the following courses must be successfully completed for the concentration. The four courses are:

Second Summer Term
Analytics Software Technology
Project Management
Problem Framing
Analytics Consulting Practicum

Analytics in Society: Security, Legal, Policy, and Enterprise Issues with Data (1.5 Credit Hours)

Big Data isn’t a free-for-all world. In analyzing and collecting data, professionals need to understand key policies and ethics arguments for handling and using such sensitive information. Course topics cover these points in relation to legal, privacy, and security concerns.

Process Analytics (1.5 Credit Hours)

Find out how data simulation assists with analyzing and designing business processes, particularly within the context of globalization, product lifecycles, and technology evolution.

Forecasting (1.5 Credit Hours)

Touching on theoretical and practical use of forecasting, this course touches on structural and time-series methods and how to use these techniques on real-time economic and financial data. In the process, you’ll conduct forecasting experiments to assess the accuracy of different models for certain data series.

Marketing Analytics (1.5 Credit Hours)

Working with market research, you’ll learn to collect, analyze, and interpret this information to make and influence business decisions. Through these processes, you’ll become familiar with Chi-square analysis, ANOVA, Regression, Conjoint Analysis, Discriminant Analysis, Cluster Analysis, and Multidimensional Scaling.

Business Analytics Practicum II: Model to Insight (1.5 Credit Hours)

During the second stage of this three-part practicum, you’ll continue your team-based project, utilizing modeling and analysis techniques to gather insights and draw conclusions from your corporate partner’s real-time data.

Digital Marketing Analytics (1.5 Credit Hours)

As more and more businesses move operations exclusively online, understand the tools used to analyze consumer behavior, essential metrics, and applying modeling techniques to gain insights, answer key business questions, and deliver actionable results.

Prescriptive Analytics (1.5 Credit Hours)

Learn about how mathematical models translate into a course of action, including formulating optimization models, performing analysis to gain insights, and communicating your findings. You’ll further explore different types of optimization models, such as product mix models, portfolio optimization, product design, capital budgeting, and production planning, and when and how to use them.

Financial and Risk Analytics (1.5 Credit Hours)

Learn capital budgeting, portfolio models, options pricing, and risk quantification methods to create financial models and assess and manage risk. 

Supply Chain Analytics (1.5 Credit Hours)

Data is increasingly essential for supply chain design and operations. Offering insight into this specific application, this course provides an overview of supplier analytics, capacity planning, matching supply with demand, inventory management, and sourcing topics.

Business Analytics Practicum III: Insight to Impact (1.5 Credit Hours)

The conclusion of the MSBA program’s three-part practicum has student teams communicating their insights and recommendations to a partnering corporate client.

Note: Program and curriculum are subject to minor changes.

* For official curricular details, complete course descriptions, and any potential electives, please refer to the current edition of the School of Business Graduate Student Handbook.

Learn More About the Master of Science in Business Analytics Curriculum

Have questions about the MSBA curriculum at Wake Forest or the program in general?Fill out a request for information form, and we’ll be in touch.