M.S. in Business Analytics
M.S. in Business Analytics – Turn Data into Actionable Business Intelligence
Be A Big Data Leader In Just One Year
An M.S. in Business Analytics will help demystify data and equip you with concrete skills you can apply in your everyday decision-making. As data volumes have grown exponentially, organizations are looking for the talent necessary to turn the data into information, knowledge and, ultimately, the sort of intelligence required to make decisions adding significant value to the enterprise. Offered both in Moraga and in Silicon Valley, the Saint Mary's M.S. in Business Analytics Program aims to develop graduates who can perform sophisticated analytics for actionable business opportunities and decisions.
What You'll Learn
Curriculum
Who Should Apply
The Schedule
STEM
Unlike similar programs at other institutions, the Saint Mary's M.S. in Business Analytics Program is taught from a business school perspective. This provides graduates with a clear employment advantage: they will not only know how to collect, process, analyze, and understand data—they will also be able to employ analytical and critical thinking skills to leverage data in making critical business decisions.
Graduates of the M.S. in Business Analytics Program will be able to:
- Perform sophisticated quantitative analysis,
- Translate data analytics into actionable business decision-making,
- Demonstrate proficiency with programming and software tools for analytics,
- Develop reasonable solutions to ethical issues in data analytics, and
- Communicate effectively in oral and written forms.
OPS 801: Data Analysis
This course equips students with the ability to apply and interpret classical statistical methodologies to analyze a business decision setting. Topics include Descriptive Statistics, Probability and Probability Distributions, Interval Estimation, Hypothesis Testing, Experimental Design, Analysis of Variance (ANOVA), and Linear Regression. R will also be introduced in this course.
OPS 802: Programming for Analytics
This course prepares students to build well-designed code modules that follow basic programming concepts and logic flow. It covers the fundamental concepts of computer programming using a standard programming language such as Python. Topics include data structures, control structures, data input/output, object-oriented programming, exception handling, and debugging. Concepts and methods introduced in the course are illustrated with simple data analysis examples.
OPS 803: Data Management Technology
This course prepares students to effectively manage data through database theory and tools. Topics include relational database structure, database queries and reports, and database management issues such as concurrency control, data security and integrity. Structured Query Language (SQL) and a structured database software package will be used in the course.
OPS 804: Advanced Data Analysis
This course is designed to equip students with advanced techniques for data analysis. It builds on the Data Analysis course. Topics include Regression, Logistic Regression, Non-linear Regression, Time Series Analysis, Nonparametric Methods, Bayesian Probability Updating, and Decision Analysis. Students will continue learning R in this course.
MGT 805: Business Communication for Data Analytics (0.5 course)
In this course students will learn how to construct arguments using quantitative data for a variety of audiences. It provides essential concepts in the formal study of argument theory, including enthymemes and syllogisms, audience analysis, and organization.
MGT 806: Ethics and Analytics (0.5 course)
This course equips students with the insight necessary to be an ethical analyst aware of the legal, policy, and ethical implications of data. Central to this is that students develop a perspective on the ethical dilemmas surrounding the data life-cycle including collection, storage, processing, analysis, and use. Topics include: an introduction to the dominant ethical traditions, privacy, data security, data property rights, data accuracy, fraud, negligence, and unanticipated outcomes as well as codes of conduct. It includes constraints and considerations for specific industry and institutional domains, data-types, and collection methods.
OPS 807: Optimization
This course prepares students to address problems and opportunities in supply chain management and business process optimization. Students will learn how to translate business scenarios into mathematical models and how to use linear programming to identify optimal solutions. Topics include Process Analysis, Linear Programming, Integer Linear Programming, Queuing Models, Inventory Models, and Simulation. A programming language (AMPL) will be introduced in this course.
OPS 808: Machine Learning for Business
This course prepares students to develop systems to measure, monitor and predict the evolution of key enterprise variables and performance indicators and present them in the form of usable information supporting the business decision-making process. Topics include project management, data warehousing, business reporting and performance management, data mining, text mining, and big data strategies.
MKT 809: Marketing Analytics
This course prepares students to model and analyze market and customer data. Topics will include applications of analytics in key marketing areas, including market segmentation, new product and service design, revenue optimization, customer relationship management (CRM), pricing and yield management, and distribution decisions. Essential marketing concepts and theories are introduced as needed, as well as cases and projects.
FIN 810: Finance Analytics
This course focuses on the applications of analytics in finance and related fields through econometric analysis and financial modeling. Concepts of financial analytics will be introduced via exercises such as: Creating a portfolio and evaluate its performance; Estimating asset pricing models using econometric techniques; Understanding and applying portfolio optimization methods; and Explore the fundamentals of options markets, and options trading. Topics will include the Capital Asset Pricing Model (CAPM), Markowitz efficient frontier, binomial trees, and the Black-Scholes option pricing model.
OPS 811: Data Visualization and Story Telling (0.5 Course)
This course prepares students to create compelling narratives to effectively transmit the results of their analysis. Students learn various techniques and tools to present analytical results visually, communicate information clearly, and articulate the business insights revealed by analytics effectively. Topics will include data visualization software packages (e.g. Tableau) to present data dynamically, visual querying linked multi-dimensional visualization, dashboards, geographical information system (GIS), animation, personalization, and actionable alerts.
OPS 813: Cloud Computing (0.5 Course)
Cloud Computing covers the fundamental topics and concepts of cloud infrastructure in order to solve large data analysis problems. Topics covered in this course include cloud architectures such as Amazon Web Services, cloud programming, cloud transport using Docker Containers, mobile cloud applications for the Internet of Things (IoT), social network analysis using cloud services, cloud performance, and cloud security.
OPS 812: Field Study
This is the capstone course of the program. Armed with knowledge and skills they learn through the program, student teams take on real-life analytics projects and will present and defend their findings and recommendations to faculty and analytics experts.
Whether you are interested in understanding how data can help consumer companies market more effectively to their target audiences, in leveraging investment trends to plot more successful portfolio strategies, or in analyzing processes to maximize supply chain effectiveness, the Saint Mary's M.S. in Business Analytics Program can help you reach your career goals.
Offered in Moraga and Silicon Valley, the M.S. in Business Analytics is a cohort-based program offered in two formats: in-person (18-months) or hybrid (12-months).
Moraga Schedule
This is an 18-month program starting in July with two classes per quarter offered on Saturdays. Students take two courses a quarter for a total of 12 courses (including the capstone Field Study course). The program’s content is delivered in a schedule format of traditional face-to-face classes. Each quarter, students will take two classes in person on Saturdays.
Silicon Valley Schedule
This is a 12-month program starting in October with three classes per quarter offered on Saturdays and Tuesday evenings. Students take three courses a quarter for a total of 12 courses (including the capstone Field Study course). The program’s content is delivered in a schedule format which includes online and traditional face-to-face classes. Each quarter, students will take two classes in person on Saturdays and one course via live web-conferencing on Tuesday evening.
Saint Mary’s offers a STEM designation for the Business Analytics degree that allows international students to receive immediate Curricular Practical Training (CPT) during the program and 36 months of Optional Practical Training (OPT) after graduation. Set yourself up to build a successful career in the ever-growing STEM field by enrolling today.
We're Making An Impact
Imani Dunbar '17
Global Analytics Leader at Facebook
Simon Perez, '18
Senior Consultant in Forensic Analytics at Deloitte
Nicole French, '18
Credit Analyst at Wells Fargo
Vinay Sharma, '18
Consultant in Cyber Risk at Deloitte
Have Questions? Schedule a one-on-one with a program specialist.
Build Your Resume While Earning Your Degree – Client-based Projects Built Into the Curriculum
Macy's
Working with the Director of Advanced Analytics at Macy's, students used Machine Learning/AI to analyze a large dataset and build a recommendation engine, so that when a customer visited the Macy's website and clicked on a garment, other similar garments could also be displayed to help the customer succeed in their search for appropriate clothing.
Google-sponsored project to help the blind
Students trained a deep neural network on a terabyte of image data to recognize objects and relationships between objects, e.g., a dog and cat with the dog chasing the cat. This technology enables folks that cannot see their surroundings to instead have these scenes described to them.
Building on Zillow's Home Pricing Models
Students used AI and built random forest machine learning models and used XGBoost to better predict the sales price of homes.
Find An Information Session
Teaching Team
Navid Sabbaghi
Professor & Program Director
Navid Sabbaghi earned his Ph.D. from the Massachusetts Institute of Technology and was awarded a National Science Foundation fellowship in recognition of his academic achievements. He has research interests in the areas of green supply chain management, portfolio management, and machine learning/artificial intelligence. He is passionate about business analytics and bringing the next generation of data scientists online to improve the world we live in.
Wenting Pan
Associate Professor
- Education: Ph.D. in Operations and Decision Technologies Paul Merage School of Business, University of California, Irvine, June 2012 Optimal Product Pricing, Order Quantities and Sourcing Strategies for an Assembly System Under Supply Uncertainty
- Recent Publications: Pan, W. & So, R. (2016). “Component Procurement Strategies in Decentralized Assemble-to-Order Systems Under Supply Uncertainty”, IIE Transactions, 48, 3, 267-282.
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Courses Taught: Operations Management, Data Analysis, Advanced Data Analysis
Ameera Ibrahim
Associate Professor
- Education: Ph.D. Management Science, University of Massachusetts, Amherst, 2014
- Recent Publications: Ghoniem, A., Maddah, B., and Ibrahim, A. (2014). Optimizing Assortment and Pricing of Multiple Retail Categories with Cross-Selling. Journal of Global Optimization, 1-19. DOI:10.1007/s10898-014-0238-3
- Courses Taught: Supply Chain Management and Business Process Optimization
Ahmed Ahmedin
Associate Professor
- Education: Ph.D. UC Davis, 2015
- Professional Experience: Former Senior Data Scientist at Polaris Wireless
Information Sessions and Events
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Sep
21Saturday, September 21, 2019 - 11 A.M.
Brother Urban Gregory HallExecutive MBA Application Prep Session...
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Sep
21Saturday, September 21, 2019 - 11 A.M.
Faculty Staff Dining RoomStart A Career In The Fastest Growing Occupation In The U.S....
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Oct
3Thursday, October 3, 2019 - 12 P.M.
Take a leap of faith and jump in. We'll dive into our various graduate business...
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Oct
3Thursday, October 3, 2019 - 12 P.M.
The MBA Information Session is intended to provide you with “insider” knowledge in...
Last updated by Hannah Ruane on July 31, 2019
Contact Us
Graduate Business 
1928 Saint Mary's Road
PMB 4240
Moraga, CA 94575
Phone: (925) 631-4888
Email: smcmba@stmarys-ca.edu
1928 Saint Mary's Road
PMB 4240
Moraga, CA 94575
Phone: (925) 631-4888
Email: smcmba@stmarys-ca.edu