Master of Business Administration in Business Analytics

The Master of Business Administration in Business Analytics provides students the depth of analytics expertise and broad business applications to tell the stories, identify opportunities and threats, and solve business problems by using data. The classes are led by professors from multi disciplines who are passionate about analytics. Students will learn from an intensive curriculum across a range of business functions and explore the latest technology and methods of transforming and translating data into meaningful information to make decisions. Specific tools include Tableau, Python, R, SAS, SQL, and Excel.

Following guidelines of the Texas Higher Education Coordinating Board (THECB), the courses are designed to create these marketable skills:

  • Perform model estimation, inference, and forecasting
  • Use descriptive, predictive, and prescriptive methods to solve business problems.
  • Practical usage of the latest methods and tools, translating data into information
  • Improve quantitative and analytical aptitudes
  • Use data mining and data visualization methods to make decisions
  • Experience in Tableau, Python, R, SAS, SQL, and Excel.
Program Summary 

Flexible duration: allows you to complete at your own pace
Total credit hours: 33 hours
Format: Online, hybrid, or in classroom
Economical: approximate total tuition of $13,000 for in-state students and $16,000 for out-of-state students. 

Concentration Courses

Data Visualization

This course will introduce data visualization - the art and science of turning data into readable figures and graphics. Multiple techniques and algorithms for creating more effective and clearer visualization will be introduced. Students will go through the process includes data modeling, data preparation, mapping data attributes to graphical attributes, and visual encoding based on known properties of visual perception as well as the tasks at hand. Students will also learn the value of visualization and how to best leverage visualization methods. The learning process will emphasize design and practical business applications.

Data Mining and Text Analytics in Business

The course will provide an overview of data mining, text analytic, and their applications to business problems. Details on the theories and algorithms will be discussed, together with their applications to real business solutions. Hands-on exposure to different data mining methods will be obtained through case studies using mainstream data mining tools. The modern text analytic framework will also be introduced.

Model-based Problem Solving

This course teaches students to use mathematical programming modeling to develop models that lead to making better decisions based on optimization giving some constraints. This includes learning about linear programming models, dynamic programming models, integer linear programming models, and nonlinear programming models. Learning about these methodologies provides students a set of tools that can be used to make decisions about the optimal use and allocation of limited resources by businesses and government institutions. 

Applied Analysis of Business Process

This course applies business process concepts, methodologies, and tools to solve real-world problems in business, government, and academic contexts. Students will develop and present solutions to problems they analyze, including business process software use, six sigma analysis, and statistical software. The course emphasizes analytical thinking in structuring problems, creating solutions, and effectively communicating those solutions to a broad audience.

Core courses

Introduction to Business Analytics

This course provides an overview of the business analytics ecosystem with introductions on three types of analytics: descriptive, predictive, and prescriptive. Applications and tools of business analytics are the focus. In addition, data foundations, as well as big data concepts, are also discussed.    

Data Modelling and Forecasting

This course teaches students to analyze and model time series data. Students will analyze data, create forecast models, assess forecast models, and forecast future data values. This includes learning about autoregressive models, autoregressive moving average models, the ARIMA model, conditional heteroscedasticity models, vector autoregressive models, and vector error correction models. These methodologies can be used to forecast business data and data from other areas.

Advanced Applied Business Statistics

The course is structured around the most commonly used SAS statistical procedures. Students will learn how to test the assumptions for all relevant statistical tests. Major topics include descriptive statistics, one-and two-sample tests, ANOVA, correlation, linear and multiple regression, and analysis of categorical data. The course focuses on the use and interpretation of SAS results while also demonstrating the logic, reasoning, and calculations that lie behind any statistical analysis.  Furthermore, the course emphasizes the application of statistical tools to real-life business concerns. 

Cost Analysis and Control

Management control systems, profit performance, standard and direct costing, investment control, and long-range planning.

Financial Administration

Theoretical and procedural consideration in administering business firm financial planning, fund raising, and controlling of firm’s finances. Specific emphasis is given to capital budgeting and cost of capital.

Current Issues in Organizational Behavior

Behavioral factors relating to issues such as automation, ethics, labor-management relations, and similar problems, with emphasis upon research and current literature.

Graduate Seminar in Marketing

An intensive study of specific marketing concepts, theories, and strategies used to market goods and services. Emphasis is placed on reading current journal articles and other related marketing publications.

Graduate Seminar in Business Policy

Analytical study of business decision making, the creation of business strategy, and the creation of sound business objectives and policies. Takes an integrating or interdisciplinary approach to the role of the organizational executive. Should be taken during student’s last spring semester.