Home MS in Business Analytics

The Online Master of Science in Business Analytics

Data science and analytics comprise the modern language that is helping to direct the future of business. The data science professionals and business leaders who understand this language, and who can render its fundamental patterns into actionable insights, have a unique power to redefine corporate strategies, enhance agility and improve profitability.

At William & Mary’s Raymond A. Mason School of Business, we offer an Online Master of Science in Business Analytics (MSBA) that is designed to help pioneering professionals embrace the power of data science and evolve their expertise in business.

You're More Than a Test Score

Visit our application requirements page to see how we evaluate prospective Online MSBA students holistically with no GMAT or GRE scores required.

Explore the Online MSBA

Discover Our Curriculum Pillars

See Tuition Information

View Application Requirements

Business Analytics Certificate

Online MSBA by the Numbers

#18

Online MSBA Program¹

32

Credits

8

Core Courses

4

Prerequisite Courses

2

Pre-Program Courses

Gain a Competitive Advantage

William & Mary faculty designed the Online MSBA program with a singular goal in mind: to give you an unmatched competitive advantage in the workplace. Our program blends the technical rigor you expect from a graduate analytics program at a top-ranked university with the strategic business insights you need to communicate productively with stakeholders.

As Faculty Director Joe Wilck says, “It is not enough to just know business analytics methodologies. You and your organization need problem solvers who can take data from chaos to clarity.”

Our expert faculty—terminal degree holders who have worked in cybersecurity, information technology, telecommunications, healthcare, marketing, manufacturing, oil and gas, and the Department of Defense—weave the theme of business intelligence and analytics throughout the program. You will learn about the value of big data and the ethics of working with algorithms as well as how to manage teams, communicate solutions and steer data-driven decision-making.

The concept of business intelligence and analytics is introduced prominently in our core course BUAD 5112 Competing Through Business Analytics. In this course, you will learn how to:

Integrate analytics into business processes
Visually convey insights from complex data sets in a straightforward, digestible way
Identify the most difficult and time-consuming steps of business processes
Create graphs with Python programs using the Matplotlib package
Create an analytics presentation with graphs you have created
Program two heuristic algorithms in Python
Web scrape

This course, and the program as a whole, will challenge you to synthesize your technical and strategic learnings so you can champion the importance of business analytics at any company.

Video Transcript

Speaker 1:
This program was designed in conjunction with our advisory board, with the mindset of what does industry need. Other programs may have technical courses, but I feel like our courses are taught by faculty that are very strong technically that translates into very rigorous experience in the classroom as far as using these techniques and understanding what lies underneath it.

Speaker 2:
The professional workforce is moving more towards a tech centric and a data centric environment. And so having skills where you can code an R on Python, and also develop on visualizations using Tableau, and managing data using Alteryx, and optimizing models using the Gurobi are very useful in the current state of the art mentality. However, our curriculum goes beyond that. We give you a foundation in those skills, but also in the knowledge so that as those softwares change, you'll be ready and you'll be a lifelong learner, but also lifetime relevant in the field.

The ability to take this program online allows us to draw a diverse set of students that bring different industry and different work experiences in different educational backgrounds to the table. It basically raises the level of the conversation. It's very much more professional. It's very much more, "How can I apply this to my business? And "Oh, that worked in your business. Well now, let's apply it to my business and see how that will work." It just raises the maturity. It raises the skills. It raises the thought for how we can compete through business analytics.

What Our Students Say

In Competing Through Business Analytics, we developed essential skills—the ability to visualize data and to use it to persuade clients—that would serve us in class, our eventual jobs and, more pertinently, our job interviews.

Audrey Low Thumbnail

AUDREY LOW

MSBA ’19 CANDIDATE

More From Audrey

From Data to Insight: Behind Our Curriculum

William & Mary's Online MSBA program is designed to maximize your computing and modeling skills while honing your ability to apply data science to strategic business planning. The program curriculum revolves around four dynamic pillars, and mastery of these pillars helps ensure that you graduate with a tangible advantage in a high-demand field, where opportunities are growing across industries and around the globe.

Explore the learning outcomes of these four pillars:

Business Acumen: Solve business problems while considering the critical needs of the business and its existing processes, strategy, and organization; share results ethically with respect to customer and client confidentiality
Math Modeling: Develop algorithms that solve problems with speed and accuracy, select appropriate methodologies to solve a problem, and construct error-free models and analyses
Computing Technologies: Program effectively in R and Python, use data wrangling to cleanse data and render it more effective in solving business problems, and effectively manage databases
Communicating With Impact: Create and deliver digestible presentations and data visualizations to audiences less familiar with the intricacies of analytical processes

These skills will guide you in asking the right questions, building the right models and using those models to perform the right analyses. The resulting insights, when appropriately interpreted and communicated, will give you the means to transform business outcomes by telling the right story, in the right way.

Plan Your Path Toward Success

It is not enough to just know business analytics methodologies. Organizations need problem solvers who can take data from chaos to clarity. The William & Mary Online MSBA program prepares individuals to do just that.

JOE WILCK

FACULTY DIRECTOR FOR THE ONLINE MSBA PROGRAM AT WILLIAM & MARY

See just how many career opportunities you could unlock with the Online MSBA—you might be surprised by the possibilities that await a tested data science professional.

See Career Statistics

Online MSBA Courses Overview

At the intersection of our four pillars—business acumen, math modeling, computing technologies and communicating with impact—are the talents and tools every data science professional may need for a successful and profitable career in business analytics. The Online MSBA curriculum prepares you to master exactly these.

Our 32-credit curriculum can be broken down into the following three types of courses:

4 prerequisite courses
1 pre-program course worth 0 credits
8 core courses, worth a total of 32 credits

Prerequisite Courses (8 credits)*

BUAD 502A Probability and Statistics I (3 credits)

In the area of probability, this course covers the concepts of discrete and continuous probability distributions as well as conditional probability. It also covers basic statistics, which can be thought of as a set of tools for interpreting data. These include descriptive statistics, which permit us to describe basic characteristics of data, including the computation of means, standard deviations and ranges of a data set. This course also covers inferential statistics, which are methods for uncovering deeper insights from the data, such as hypothesis testing. Finally, the course considers data visualization as an integral part of data analysis.

View Full Description

BUAD 502B R Programming (1 credit)

This course provides a set of programming skills using the R programming language, which is widely used in business analytics for statistical computations.

View Full Description

BUAD 502C Python Programming (1 credit)

This course provides a foundation of Python programming skills for business analytics including knowledge of Python data types, facilitating repeated execution through the application of loops, using conditional statements, programming the input and output of data, the use of Python packages, and the construction of functions.

View Full Description

BUAD 502D Linear Algebra for Business Analytics (3 credits)

This course provides a set of linear algebra tools for performing business analytics including vector-matrix multiplication, Gaussian elimination, computing determinants, computing matrix rank, computing matrix column and row spaces, performing eigenanalysis, and performing principal components analysis.

Pre-Program Courses (0 credits)

Excel Boot Camp (0 credits)

Completion of this course ensures that students have sufficient skills in Excel. This non-credit course will be available in Canvas throughout the program for students' reference as needed.

Core MSBA Courses (32 credits)

BUAD 5112 Competing Through Business Analytics (4 credits)

This course will include a survey of the state-of-the-art in business analytics, examining companies that have used business analytics for competitive advantage and how they have done so. This course will teach business acumen and how the field of analytics fits within the context of business. Topics will include business metrics as used for performance measurement and incentives, communicating with impact, visualization, and the functions of a company—how they interact, what data they have, and their development and deployment of algorithms. The course will also include a survey of opportunities for problem solving using business analytics in operations, supply chain, human resources, finance and marketing, as well as an introduction to the tools that are covered in the remainder of this program.

BUAD 5052 Decision Modeling (4 credits)

Probability and Statistics is a foundation course in the study of business analytics. It provides an understanding of the principles associated with modeling of stochastic processes. The topics will include probability theory—important probability distributions, sampling from distributions and the interaction of multiple stochastic processes; regression; statistical analysis—descriptive/inferential/predictive statistics, multivariate statistics and time series models; and modeling—modeling concepts, Monte Carlo simulation and decision analytics. Students will also be introduced to a variety of statistical modeling packages.

BUAD 5772 Database Management and Visualization (4 credits)

Organizations store data in two types of databases: operational and analytical. Operational database topics include database requirements, entity relationship modeling, relational modeling database constraints, update anomalies, normalization, Structured Query Language (SQL) and data quality. Analytical database topics include data warehousing concepts, dimensional modeling (star schemas), data warehouse/data mart modeling approaches, the extraction/transformation/load (ETL) process, online analytical processing (OLAP)/business intelligence (BI) functionalities and the data warehouse/data mart front end. Once data is cleaned and stored, data visualization is used to most effectively communicate information contained in the data. The course covers data visualization principles drawn from the fields of statistics, perception, graphic and information design, and data mining. Students will learn visual representation techniques that increase the understanding of complex data and models. Topics include charts, tables, graphics, effective presentations and dashboard design.

View Full Description

BUAD 5122 Machine Learning I (4 credits)

This course is designed to provide students with a deep understanding of the theory and practice of regression and classification, two of the most commonly used techniques in the data scientist's toolkit. These predictive analytics techniques are important members of a family of analytics often referred to as machine learning techniques. The programming language R is used extensively in labs and assignments in this class and subsequently reappears in other classes throughout the program.

View Full Description

BUAD 5132 Machine Learning II (4 credits)

This course is designed to provide students with a deep understanding of machine learning and big data, including more elaborate techniques that extend the coverage from Machine Learning I. The data storage and retrieval techniques that have served the information processing industry for decades have proven inadequate in the face of the huge collections of data presently being created by the internet and the so-called "Internet of Things." Businesses today require a new set of technologies that are specifically designed to deal with these huge data sets. In this course, the Hadoop environment and Amazon Web Services (AWS) will be used to process large-scale data sets.

BUAD 5092 Optimization and Heuristics (4 credits)

Optimization is an analytics methodology designed to yield the best solution to a given problem. Students are exposed to theory and applications of optimization including linear programming, non-linear programming, discrete optimization and specialized networks. This course includes discussion about the difficulties of accurately representing real-world processes with a mathematical model. Most business problems are too large or too complex to be solved optimally, where the strict definition of "optimal" means finding the provably best solution. Finding a solution that approximates the optimal solution is, therefore, the predominant mode of problem solving found in industry: these are called heuristic solutions. Many companies gain a competitive advantage by constructing heuristics that either find better solutions than do their competitors or find solutions more quickly. This course focuses on achieving such results by programming custom algorithms, which are a sequence of steps taken to provide a solution to a problem.

View Full Description

BUAD 5802 Artificial Intelligence (4 credits)

The theme of this course is "natural models and artificial intelligence." The course considers natural models of intelligence and their artificial equivalents. It shows how viewing natural intelligence is an effective mindset and it describes the key analytics tools required for designing and executing some business processes competently. A majority of the course is devoted to the topic of neural networks, although other methods are included, such as genetic algorithms, simulated annealing and swarm intelligence.

BUAD 5762 Business Analytics Capstone Project (4 credits)

This experiential practicum course includes a comprehensive business analytics project that the student will complete from start to finish, integrating the skills that have been acquired from their previous coursework in the business analytics program. They will define and frame a complex problem, develop a systematic approach to solving it using analytics, identify methodologies that are suited to the problem, quickly prototype solutions with those methodologies to identify the best approach, and, ultimately, generate an innovative solution and persuasively convey that solution using data visualization techniques and communication skills.

*Note: BUAD 502A, 502B, 502C and 502D are prerequisites for the remainder of the program. Students may be able to satisfy these prerequisites with courses from other sources, and they should inquire about their eligibility during the admission and onboarding process if they wish to do so.

Video Transcript

Monica Tremblay:
So companies all have data, but what they need is information. So what we teach in the MSBA is how to take that data, clean it, process it, analyze it, and then tell the story that's behind that data.

So one of the projects that we do in my database and data visualization class has to do with Medicare claim. And we take these claims and we try to understand 30-day readmissions. So we organize and clean the data that wasn't created with the purpose of figuring out 30-day readmissions, it was created with the idea of billing. But we take that data and we organize it, we calculate what a 30-day readmission looks like, which patients were admitted after 30 days, and then we do data visualizations to try to figure out patterns in those readmissions with the goal of hoping hospitals minimize those readmissions.

Joe Wilck:
One of the examples of how we bring business back into the curriculum, in the machine learning courses, we spend a lot of time talking about recommender systems. Recommender systems are all around us, whether it's Amazon telling you, "Add this to your cart since you have these other things in your cart," plus your prior purchase history, or whether it's LinkedIn saying, "Connect with this person because they're a friend of a friend," or whether it's Netflix telling you to watch this movie.

Now we've all experienced recommender systems as customers, how can we use those and how can we build those so that they can be taking that data very quickly and then analyzing it very quickly so that within one second, we can provide that back to the customer. We can tell them, "Hey, buy this," or "Link up with this person." That's what we cover in the machine learning class and that's relevant to all businesses.

Many of our faculty come from an engineering or STEM background. And in many of those types of programs you have a Capstone Project that culminates the end of your education, whether at the undergraduate level or at the master's level. So for us, it seemed natural to have a capstone project, to showcase the student's abilities from start to finish. Finding the business problem, setting goals, exploring the data, setting up a system to collect the appropriate data, developing models, using programming and other techniques they learned in the program. Then actually coming up with ways to visualize those findings and then make recommendations and hopefully deliver value. The Capstone course and the Capstone Project provide that opportunity to the student to do that with a real world client and get real world feedback. It's a resume booster, just a way to show that you are a data science and business analytics professional.

The Online MSBA at a Glance

Complete in as few as 15 months^**
100% online
No residency or on-campus requirement

3 starts per year: August, January and May
Earn your degree from a prestigious business school
Study with our faculty of industry experts

^{**Students who are required to complete the prerequisite courses can graduate in as few as 18 months.}

Want More Insight?

Take a look at what’s ahead in the Online MSBA program—download our program details guide, your one-stop document for admissions requirements, courses and more.

Download the Guide

Discover Our Online Experience

online classroom thumbnail

See the Online Classroom

smiling woman wearing blue jacket and glasses

Capitalize on Career Development

photo of WM faculty building

Meet W&M Faculty

The Workplace Value of the Online MSBA

Master Critical Thinking and Data Analytics Online at W&M

Master Critical Thinking and Data Analytics Online at W&M

Master Critical Thinking and Data Analytics Online at W&M

Video Transcript

Joe Wilck:
I consider the MSBA to be the MBA of the 21st century. Many professionals today have the technical aptitude, and then there are other professionals that have the communications aptitude. But it's the combination of those two skills that is really lacking in today's industry. And that is what our degree is trying to provide. Someone who can do the business acumen and communicate that value, but also has the technical skills to develop that value. We call those unicorns. And in the data science and business analytics field, that is what we're trying to produce.

Monica Tremblay:
What's great about the MSBA at William & Mary, is that it sits at the intersection of critical thinking, problem solving, and data analytics. And that's the sweet spot that I think employers are looking for. It's not enough that you have the skills to analyze data, but you also have to know what to do with it and what it leads to. And we live in a world or a sea of data, you could go many paths. But how do you land on those things that are important? And that's where critical thinking and problem solving comes in.

Joe Wilck:
So our program is unique in that we have two courses in machine learning, a course in artificial intelligence, a course in optimization, a course in databases, and follow on courses for our capstone. Most programs teach you R and Python as part of the curriculum. We require it before you get to the curriculum. So we're able to take you further technically, but also that allows us to actually show you how to use these skills in a business sense. These skills can help you at any point of the company, whether you're at the analyst role, the manager role, or the executive role.

Monica Tremblay:
So in today's world, almost everything is data-driven. It's no surprise that the largest companies in the world right now are data companies. Amazon is a data company. Google is a data company. Facebook is a data company. So companies are now having to make their decisions based on data.

Joe Wilck:
Our program is designed to be relevant for a number of different people, whether you're someone who is a seasoned professional, but you're looking to transition into a data science or a business analytics role, so you're just looking to add that technical expertise onto you're already well-established business acumen. For someone who does not have a lot of experience, but realizes they want to be in that technical role, so they're trying to get a master's degree to kind of get a seat at the table if you will. Then there's another group where they're looking to be a manager or a leader, and perhaps they already have an MBA, but they need more technical expertise to help drive and deliver value for their business and to manage their teams.

We are teaching you skills and knowledge and a foundation that will not only help you in the job market, but also help your company on the stock market.

Today’s corporate leaders are increasingly challenged to find qualified employees who understand data science and have proven experience applying its key business functions. Those who could fill this need must be familiar with unstructured data dumps, machine learning, data visualization and current analytics tools, but they must also be able to interpret the information acquired through these means and effectively communicate its implication(s) for the organization's bottom line.

By weaving our curriculum's four key pillars of business acumen, math modeling, computing technologies and communicating with impact into each of our Online MSBA courses, we blend the essential elements of business expertise with a robust portfolio of data science offerings. The result is a dynamic program with real-world applicability that ensures our students graduate with a thorough understanding of how to effectively apply their findings and communicate their insights in a succinct, coherent manner.

WHAT OUR STUDENTS SAY

What brought me back to school was kind of looking at the changing landscape, professionally. I didn’t want to be pigeonholed into computer science or statistics, strictly one of those two, nor did I feel like the general approach of an MBA was right for me either. I like the intersection of the two, which is what led me to business analytics. There are a lot of possibilities.

ANDREW LIEBERMAN

MSBA ’18

Redefine the Bottom Line

2.35 Million

Data science and analytics jobs posted in 2015²

#1 Best Job in America

Data Scientist³

$110,000

Median base salary for data scientists³

27%

Percent of data science roles requiring a master's degree⁴

2.7 Million

job openings expected by 2020 for U.S. data professionals⁵

Meet Our First Online MSBA Cohort

William & Mary’s Online MSBA program welcomed its first cohort in spring 2018, and we quickly discovered that our student demographics mirrored the personal and professional diversity that is common in the fields of technology, data analytics and programming. While some of our current students have highly technical backgrounds, others come from financial, educational and even military ones. They represent varied sociocultural contexts and reside in geographic locations across the country. It is telling, then, that our program has managed to meet each of these driven individuals where they are, and that they’ve found it able to help them advance their technical and managerial development.

Take a look at the story told by our cohort demographics, and consider what you could learn not only from our Online MSBA curriculum and faculty but also from such a diverse cohort of peers.

Not interested in our Online MSBA? Check our our one-year residential MSBA program..

A Closer Look at Cohort No.1

30% U.S. minorities
15% W&M alumni
5 average years of work experience
3.3 average undergraduate GPA (on a 4.0 scale)
62% ages 26-45
15% work in educational services
15% work in financial services
15% work in technology

^{NOTE: Statistics are based on cumulative self-reported W&M Online MSBA student profile data collected from the spring 2018 cohort.}

I want to...

Explore Program Costs

View Application Requirements

Read Admissions FAQs

View Other Graduate Programs

What skills will you acquire in the Online MSBA?

Querying relational databases using SQL
Performing extract, transform, load (ETL) processes
Building data warehouses
Preparing data for analysis using data wrangling techniques
Managing data using services such as Hadoop, Amazon Web Services and NoSQL
Creating data visualizations and dashboards with Tableau
Performing descriptive, predictive and prescriptive analyses
Utilizing basic methodologies like regression, logistic regression, time-series analysis, Bayesian methods, etc.
Deploying a broad array of machine learning and artificial intelligence techniques
Constructing and executing prescriptive optimization models
Analyzing data with statistical software including R
Writing computer programs in Python and R
Designing, programming and implementing heuristic algorithms in Python
Conducting simulation analyses
Distilling strategic insight from analyses and communicating it persuasively

Get to Know the Raymond A. Mason School of Business

photo of WM faculty building

About the Raymond A. Mason School of Business

gentleman in jacket and tie holding up an ID

Hear From Our Alumni

woman in black blazer and pink shirt with open hands speaking with woman in beige blazer

Find Student Support

professionally dressed graduate student smiles

Explore all Mason Graduate Business Programs

Interested in Our Online Programs?

Oct

21

Priority Application Deadline

October 21st

Spring 2023 Term

Dec

12

Application Deadline

December 12th

Spring 2023 Term

Jan

9

Next Start

January 9th

Spring 2023 Term

Email your questions to an Admissions Advisor

Schedule a call to speak with an Admissions Advisor

Speak with an Admissions Advisor right now by calling 844-234-4075

Sources

Retrieved on February 7, 2022, from usnews.com/education/online-education/college-of-william-and-mary-OBUS0134/business
Retrieved on August 22, 2018, from burning-glass.com/infographic-data-science-jobs-by-the-numbers/
Retrieved on August 22, 2018, from glassdoor.com/List/Best-Jobs-in-America-LST_KQ0,20.htm
Retrieved on August 22, 2018, from pwc.com/us/en/library/data-science-and-analytics.html
Retrieved on August 22, 2018, from forbes.com/sites/louiscolumbus/2017/05/13/ibm-predicts-demand-for-data-scientists-will-soar-28-by-2020/

Questions? Let’s Connect.

Apply Now

Get More Info