Academics
Format
Students can complete the program in-person or schedule a mix of on campus and online courses.
Adjustments can be made from semester to semester.
Schedule
To accommodate busy professionals, our classes are primarily offered in the evening and online. You can complete your degree in just four semesters (16 months), with convenient spring and fall start options.
FREE
Experience Class for Yourself
Join us on campus for a class from faculty member Matt Pecsok. You will have the opportunity to attend class, ask questions, make connections, and see what MSBA is all about.
Tuesday, March 11 |
5:30 pm - 7:00 pm MT
| On Campus
Registration
https://go.eccles.utah.edu/l/356541/2025-01-24/4ggj45m
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Curriculum
Our business analytics curriculum provides students with the skills and knowledge to navigate the intersecting landscapes of business and data analytics. The hands-on coursework integrates concepts from marketing, operations, and information systems — equipping students with diverse perspectives and practical experience needed to succeed in a competitive job market.
Our curriculum contains 30 total credits, comprised of 27 core credits and 3 elective credits:
Core Courses
Course Number: IS 6420
Credits: 3
Advanced topics in database theory and design, including hands-on development of a working database system. Topics covered include the relational database model, foundations in relational algebra, design techniques, SQL, distributed databases, multimedia databases, and knowledge bases.
Course Number: IS 6482
Credits: 3
This course introduces data mining technologies that assist in discovery of reliable, understandable and useful patterns in structured, semi-structured and unstructured data. Students will practice core data mining technologies, analyze cases, and explore real world applications and issues.
Course Number: IS 6491
Credits: 1.5
Data Visualization is the graphical representation of information. Data Visualization and related technologies create value within organizations by providing insight from complex sets of data by communicating key aspects therefrom. This course focuses on how to increase the likelihood of action based on insights from data by telling stories with data that leverage effective Data Visualizations. The course includes a mix of theory and hands-on application using contemporary processes and Data Visualization technologies.
Course Number: IS 6493
Prerequisite: IS 6489
Credits: 3
Successful corporations can utilize data science techniques to help drive business decision making by analyzing datasets of varying sizes. In this course, a hands-on practitioner’s approach is taken to learning the fundamental knowledge, techniques and tools required for leading data science teams and analyzing big data. This course will utilize popular open source technologies and libraries in use today to learn how to collect, pre-process and visualize data, as well as build and test models for inference and prediction. We will examine the unique challenges posed by big data and complex models, and learn how to address them using distributed computing frameworks such as Dask, Hadoop and Spark. The course is taught in Python, and will offer a bootcamp in the first few weeks to help everyone get comfortable with the language.
Course Numbers: IS 6496
Credits: 3
Over three semesters students complete a capstone experience involving career development, planning, and execution. Students work in a team to complete an analytics project for a business or nonprofit organization. Sponsor organizations represent a variety of industries, including operations, healthcare, and marketing. Students capture, organize, and analyze data — ultimately making recommendations to their sponsor organization based on their findings.
Course Number: MKTG 6487
Credits: 1.5
This course introduces students to the main elements of business analytics. The domains include framing the business problem, framing the analytics problem, managing data, selecting the methodology, building the model, deployment and life cycle management. Students will learn and practice the domains using small projects.
Course Number: MKTG 6600
Credits: 3
The aim of this course is to use algorithms to reach business decisions. The focus will be on understanding the implications of analytics for the formulation and implementation of business strategy. Students will learn about a business situation, learn of an analytic method that can be used to solve the business problem, and use the method in R to solve the business problem. Supervised and unsupervised algorithms such as regression, support vector regression, customer lifetime value, clustering, text analysis, word embedding, and causal methods such as A/B testing would be used to solve business problems such as market segmentation, brand positioning, customer satisfaction, ethical decision-making, financial decisions, healthcare decision-making, product pricing. The following process will be used for each topic: Understanding the Business context -> the data that can help solve the problem -> the analytic method that could be used -> understanding the mathematics and scope of the method ->implementation using R -> combining the business context and the algorithm in a mini-project.
Course Number: MKTG 6620
Credits: 3
Business Analytics is a strategic asset that offers unique opportunities for competitive advantage. It lives at the crossroads of business and technology. As technologies transform the marketplace, companies across the globe are collecting an enormous amount of data that can be used to predict the consequences of alternative courses of action and guide decision-making. The objective of this course is to i) demystify the world of big data analytics and ii) show applications of analytic tools across everyday business decisions. Some of the topics discussed will be applications of supervised, unsupervised machine learning, outlier analysis, and adaptive learning.
Course Number: MKTG 6640
Credits: 3
The web is replete with unstructured data in the form of emails, tweets, blogs, customer reviews, and so on. This course introduces the tools and concepts that allow businesses to analyze textual data and shows how these methods can be used to make better business decisions in online and offline contexts. The course focuses on different analytical techniques and algorithms including preprocessing, text classification, text clustering, topic modeling, document summarization, and sentiment analysis. These methods are applied to different areas of business including marketing, human resource management, business law, accounting, and finance.
Course Number: OSC 6610
Credits: 1.5
Managerial decisions – regardless of their functional orientation – increasingly leverage quantitative models to approximate business problems and provide insights. This course takes a managerial approach to analytical modeling to analyze problems in a wide array of fields such as finance, marketing, operations, information systems, etc. The tools covered in this class are deterministic optimization techniques including linear programming, network models and integer programming.
Course Number: OSC 6611
Credits: 1.5
Like OIS 6610, this course takes a practical approach to analytical modeling. While the emphasis in Analytical Decision Models 1 was on deterministic optimization techniques, models in the course will be probabilistic in nature. The main topics for the course are advanced queuing and simulation. Applications will encompass problems from a variety of business disciplines including production/operations management, marketing, and finance.
Elective Courses
Students can typically choose any analytics-based course available in the Eccles School of Business as an elective.
Statistics & Predictive Analytics is strongly recommended for students without a strong a background in statistics.
Course Number: ACCTG 6210
Credits: 3
This course focuses on strategic cost management issues. Emphasis is placed on aligning cost system functions with strategy. This course identifies, develops, and uses management accounting information for value chain analysis, strategic positioning, and cost driver analysis.
Course Number: ACCTG 6610
Credits: 3
This course is designed to make you an effective reader and interpreter of financial statements. Most of you have put in considerable time learning how to prepare financial statements. But, the knowledge base and skill set you have developed to become an effective preparer are not the same as those that you need to become an effective reader. Ergo, this course. Being able to effectively read and interpret financial statements is a crucial part of becoming a successful businessperson. The reason for this is simple: Successful businesspeople attract investors; investors want a return on their invested capital; and, financial statements are the primary source of information about what this return has been and will be. With this in mind, we begin the course by learning how to calculate and interpret return on invested capital (i.e., ROIC), its components, and other key performance indicators (i.e., KPIs). Understanding how to calculate and interpret KPIs is important, however, KPIs are only as good as the accounting numbers underlying them. Hence, in the second part of the course, we focus on how to evaluate accounting quality and, if necessary, make accounting adjustments that improve the informativeness of the reported numbers and the KPIs that are based on these numbers.
Course Number: ACCTG 6620
Credits: 3
The use of financial statements to analyze growth, profitability, efficiency, liquidity, and other economic characteristics of publicly-traded companies. The analysis focuses on developing an understanding of strategy, operations, industry, competitive environment, and risks with the aim to estimate valuations for investment decisions. In addition to the listed prerequisites, students are strongly encouraged to have also taken ACCTG 6610.
Course Number: IS 6480
Prerequisite: IS 6420
Credits: 3
The data generated from ongoing operations of businesses and not-for-profit enterprises continues to grow. Using the data to diagnose problems and assess opportunities is becoming more and more of a competitive advantage in today’s business environment. Before analysis can take place, existing data must be modeled in ways that facilitate reporting. This course briefly presents the data models of existing operational systems and then contrasts those models to dimensional models used in data warehouses and analytic processing engines. Business reporting needs are analyzed, data warehouses are modeled based on the reporting needs, and then SQL is used to create and populate tables based on dimensional models. Once in place, the data warehouse is used as a backend for a reporting tool to create reports that answer business questions.
Course Number: IS 6489
Prerequisite: IS 6487
Credits: 3
This is a graduate level course in statistics, with an emphasis on developing predictive models using an open source statistical programming language. The engaged student should expect to develop foundational skills for data analysis. Topics covered will include some or all of the following: descriptive statistics, nonparametric regression, probability distributions, linear and logistic regression, tree-based methods, model assumptions and model checking, cross-validation, simulation, resampling, visualization, and reproducible research.
Course Number: FINAN 6380
Credits: 3
The course transitions students from understanding finance theory to implementing financial models based on real data and using statistics, probability and econometrics, quadratic optimization with matrix algebra, accounting, duration immunization and risk-neutral option modeling techniques. The models are built in Microsoft Excel through hands-on exercises in class and at home. The models covered include but are not limited to asset return calculations and statistics, efficient frontier and portfolio diversification theory, regression index models and investment performance analysis, discrete and closed-form option pricing models, bond valuation functions, duration matching and asset/liability management of pension portfolios, equity growth models, pro-forma accounting statement construction and leveraged buyout models. To ensure success, students coming to the class should have already taken an investments class or should be taking it concurrently.
Prerequisite: ‘C-‘ or better in FINAN 6040
Course Number: FINAN 6400
Credits: 3
This course provides students with a practical introduction to the fixed income market. Focusing in particular on interest rate products such as bonds, swaps, futures and forwards. The objective is to understand the principles driving this market. In particular we will focus on the pricing and hedging of interest rate products, paying close attention to trading strategies. Topics include: arbitrage-based pricing; yield, duration and convexity of bonds; swaps both single and multiple currency; building yield curves; using the yield curve to price and hedge instruments; bond futures; understanding factors that go into making trades and offsetting risk. This course will also emphasize various mathematical tools used to price and hedge a wide variety of interest rate products.
Course Number: MKTG 6730
Credits: 3
This course is designed to increase students understanding of the key issues, theories, strategies and tactics associated with advertising and marketing communication decisions. Specifically, the course adopts an integrated marketing communication perspective and aims to provide analytical skills useful for the planning, implementation, and evaluation of various elements of the communications mix, including advertising (conventional and internet advertising), sales promotions, and public relations. Strong emphasis is placed on understanding the strategic, neurological, and psychological principles in consumer behavior which facilitate the development and implementation of marketing communication programs. This course is intended for students whose career plans involve making marketing decisions to solve contemporary business problems. Discussion of cases and news articles pertaining to the latest trends and critical developments in advertising is an important component of this course.
Course Number: MKTG 6770
Credits: 3
This course examines how insights from research in behavioral economics, judgment and decision making, and social psychology can enable businesses to develop more effective and targeted marketing strategies. Central themes include a detailed analysis of how humans form preferences and beliefs as well as how a variety of motives and situational forces can affect consumer choices and evaluations. Combined, these topics have important implications for consumer-directed marketing. Students will gain an understanding of core concepts from behavioral science and will also gain experience in applying these ideas toward addressing marketing problems.
Prerequisites: MKTG 6090
Course Number: OSC 6425
Credits: 3
Six Sigma is a philosophy and set of concrete tools designed to reduce variation in all critical processes to achieve continuous and breakthrough improvements that impact the bottom line of an organization and increase customer satisfaction. In this course, we will study the five phase DMAIC (Design-Measure-Analyze-Improve-Control) approach in detail with a combination of lecture, small group breakout sessions, and hands-on practice. Course topics will include a review of statistics, process improvement tools, statistical process control, measurement system evaluation, capability analysis and design of experiments. Statistical software such as Minitab will be required and used throughout the class.
Recommended Preparation
Students who are new to information systems should consider studying foundational concepts before starting the program. There are numerous free and affordable resources available online. A popular option is this free online CLEP Information Systems course from Modern States.
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Specialization Opportunities
Our goal is to see students land top jobs in business analytics; Specialization opportunities can give students a competitive edge and help them stand out in the job market.
Graduate Certificates
MSBA students can pair their degree with a graduate certificate to diversify their skill set.
The Graduate Certificate in Cybersecurity Management (GCCM) is designed to provide foundational education in cybersecurity leadership. The certificate coursework empowers developing leaders to design, implement, and operate a security program intended to reduce risk of compromising an organization’s data. Graduate students who obtain this certificate will be better equipped to aid in the design, operation, and monitoring of security controls to protect corporate and consumer data in an age of ever-increasing aggression and sophistication.
How to Apply
Students can apply for the GCCM as soon as they are admitted to the program.
Additional Information
For more information visit the GCCM page or meet with an admissions advisor.
The Graduate Certificate in Information Systems (GCIS) program allows students to gain specialized knowledge in information systems. Obtaining a graduate-level certificate in information systems can provide an advantage to those seeking to advance their careers in the field or strengthen their technical proficiency.
How to Apply
Students can apply for the GCIS as soon as they are admitted to the MSF program.
Additional Information
For more information visit the GCIS page or meet with an admissions advisor.
The Graduate Certificate in Operations and Supply Chain Management allows graduate students to gain specialized knowledge about how firms create and capture value. Students will learn how to maximize quality relative to expenses, optimize supply chain activities, and lower production costs while managing process flows. The courses will explore strategic choices for different industries and operational objectives. Students will learn how to manage inventory effectively, utilize information systems with their supply chains, and gain real-world practice in presenting operational results to management and/or other operations personnel.
How to Apply
Students can apply for the GCOSC as soon as they are admitted to the program.
Additional Information
For more information visit the GCOSC page or meet with an admissions advisor.
It’s estimated that by 2040, the Mountain West will double in population to more than 30 million people with nearly 20 million jobs. Most of the existing built environment will be rebuilt. Several trillion dollars will be spent on development in the region over the next generation and professionals with real estate expertise will play a leading role in the transformation.
How to Apply
Students can apply for the GCRE as soon as they are admitted to the program.
Additional Information
For more information visit the GCRE page or meet with an admissions advisor.
Concurrent Degrees
Our MSBA program can be completed concurrently with another graduate degree for a robust, multifaceted education.
Students can pursue an MBA concurrently with an MSBA. Accelerate your career in business management by combining both degrees. You’ll exit the program with a world-class education and the quantitative skills needed to immediately advance your career.
Completion Time
- Full-time MBA students can complete the program in 4 semesters.
- Professional MBA and MBA Online students can complete the program in 8-9 semesters.
Students can pursue a Master of Science in Business Analytics (MSBA) concurrently with a Master of Science in Finance (MSF). Students who pursue both degrees will possess a unique skillset, blending financial acumen with the ability to extract actionable insights from data, creating opportunities in areas like quantitative finance, risk management, and investment analysis. As the financial industry increasingly relies on data-driven decision-making, graduates could lead the way in developing innovative financial models and strategies.
Credit Hour Breakdown
- MSF Credits: 30
- MSBA Credits: 30
- Total Credits: 60
Completion Time
- Full-time students can complete the program in 7 semesters.
- Part-time students can complete the program in 10 semesters.
Let’s Connect
Our admissions specialists are happy to discuss any questions or concerns you might have about the application process, admissions requirements, or any other aspect of the program. We’re eager to meet you and provide personalized support as you explore our program.
MSBA@Utah.edu
David Eccles School of Business
Robert H. and Katherine B. Garff Building, Room 2350