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Master of Business Administration with a specialization in Business Analytics

With three electives from among the courses available in the Master of Science in Business Analytics program, the Master in Business Administration with a specialization in Business Analytics is taking complex data, analyzing statistics, and finding eye-opening insights that help organizations of all types make informed, data decisions. Courses in data mining, enterprise analytics, data warehousing, and visualization will help you dissect business problems and opportunities.

Admission Requirements & Courses

Program Details

Next Start Date
Summer II Module
Application Deadline
Estimated Program Length
Credit Hours
Course Length
Cost Per Credit

About the Program

The MBA Specialization in Business Analytics allows students to choose three electives from among the courses available in the Master of Science in Business Analytics program. These courses prepare managers in all contexts to solve problems which require the application of sophisticated business analytics techniques. Topics include R and Python, data visualization, data mining, decision modeling and optimization methods, machine learning, text mining, social media analytics, health information analytics, information security analytics, spreadsheet modeling, and enterprise analytics. These courses heavily emphasize hands-on skills in data analytics, using cases and examples drawn from real-world organizations in many domains.

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An examination of financial and managerial accounting theory and concepts and their application in financial and managerial decision making. Does not count towards the MACC degree.
This course introduces fundamental concepts of financial tools and analysis for making effective managerial decisions. Topics include the role of the financial manager in the organization, decisions affecting the internal management of the firm, financial statement analysis, and operational planning and budgeting.
An introduction to statistical methodology to include probability concepts, inference techniques, analysis of variance, regression analysis, chi square and other non-parametric analyses. This course focuses on the use of the computer in performing statistical analysis.
The objectives of this course are to review certain elements of financial reporting, to develop financial analysis skills, and to gain experience in using accounting information for decision making. Prerequisite(s): ACCT 6301 or ACCT 2301 and ACCT 2302 or equivalent.
This course applies economic analysis to managerial issues in the business world. Specific topics considered include demand analysis, production and costs, pricing policies, and market structures. Extensive use is made of case analysis.
The study of advanced topics and cases incorporate managerial finance. The course builds on the foundation finance course; and covers topics including valuation of securities, valuation of the business and investment decisions, capital structure, cost of capital, mergers, and acquisitions, working capital management, international corporate finance, and risk management. Prerequisite: FINA 6303 or FINA 3380 or equivalent.
Alternative approaches to managing the resources (computers, networks, software, data, & people) that organizations utilize in applying information systems. The roles of the user/manager identifying opportunities, obtaining computer applications and creatively using information technology to improve operational, tactical and strategic planning and performance. Topics that will be covered include enterprise systems, managerial support systems, decision support systems, e-commerce applications.
This course is an advanced study of marketing policy and decision-making based upon a consumer orientation, innovation and creative adaptation to change, the cultural implication of marketing activities, and the role of theory in marketing. It investigates how marketing affects overall corporate and business decisions and gives students an opportunity to look at high-level strategic marketing decisions in product planning, promotion pricing, and distribution.
An analysis of formal organizational theory and the interrelationship of individuals in organizations. A study of the organization as a system of authority, status, leadership, direction, culture, ethics, communication and influence.
The study of the role of the production function in the business system and its relationship to marketing and finance. The focus is on the decision-making necessary for productivity improvement in the transformation process of manufacturing and non-manufacturing service organizations. Strategies of production system design, capacity management, quality management; production planning, inventory planning and control, facility location and supply chain management are explored. Systems studies include Just-in-Time, Total Quality Management and Flexible Manufacturing Systems.
This capstone course integrates knowledge in functional areas and covers strategy formulation, implementation and evaluation. Different types of organizations in all kinds of environments and industries are studied. Technology, culture and ethics are important environmental variables considered.
Business research techniques and methodologies. Topics include scientific method, business information sources, research proposal development and evaluation, research design, scaling and instrument design, sampling design, statistical packages and applications, research reporting and writing and ethical considerations in business research.
This course provides the knowledge about fundamentals of health Information Systems and the role of Information systems in efficient operation of healthcare organizations. The course specifically focuses on: Evolution of HMIS, HMIS components and basic HMIS functions, technology infrastructure for healthcare organizations, basic concepts such as HER, HIE, CPOE, and CDSS, HMIS standards such as HIPPA, HL7, and DICOM, strategic information systems planning for healthcare organizations, systems analysis and project management, information security issues, and role of HMIS professionals in health organizations.
This course seeks to address the second objective of the MSBA program, "Students will use contemporary information systems and analytical tools to acquire and manage data for business analytics." By completing this course, the students will build skills to acquire, create, examine, and manage healthcare data. The course introduces students to contemporary sophisticated data management and analytics software that is most used by the healthcare industry. The students will develop competency in data formats, data conversion, data export-import, data acquisition and cleansing, data dictionary and data manipulation methods, setting domains, constraints, optimum data types, advanced SQL queries, data visualization, and management of data resources including backups and restore.
This course teaches students how to apply computing tools to novel analytic challenges in organizational contexts. For a series of organizational analysis case problems, students will learn how to choose appropriate data, store and format it for analysis, create customized computing solutions based on programming and scripting languages, and present the results in a variety of forms, including tabular and graphic/visualization methods. Students will apply software languages such as R and Python, in desktop, cloud, and high-performance computing contexts
This course introduces students to the concept of social media analytics and techniques used to analyze social media data such as texts, networks, and actions. Students will learn how to extract data from popular social media platforms and analyze such data using software tools such as R to identify trends, sentiment, opinion leaders and communities.
This course introduces students to data visualization and dashboarding. Students will learn best practices in data visualization, data retrieval using a structured query language (SQL), polish analytical skills, and learn how to design dashboards to support managerial decisions. Students will have the opportunity to gain hands-on experience in data retrieval and visualization. Students will use Tableau as their main tool for data visualization and dashboarding but will develop transferable skills which can apply to the most common software packages in the field.
This course provides students with knowledge and skills in the various decision analytical techniques for managerial decision making including big data analytics. A number of well-defined data mining techniques such as classification, estimation, prediction, affinity grouping and clustering, and data visualization will be covered. The Cross-Industry Standard Process for Data Mining (CRISP-DM) will also be discussed. The data mining techniques will be applied to diverse business applications including target marketing, credit risk management, credit scoring, fraud detection, medical informatics, telecommunications, and web analytics.
This course introduces students to the management and coordination of enterprise data resources to improve enterprise-wide decision-making. Students will learn how to identify key performance indicators from enterprise data, how to differentiate enterprise analytics from other forms of analytics, how to determine what proprietary data will provide analytical advantage to maximize the impact on the enterprise, recent technologies for analytics and best practices from recent cases. Students will engage in an iterative process of exploring data from multiple functional areas within an organization to derive actionable insights as well as communicate findings to help enterprises improve the quality of their decisions.
This course provides students with comprehensive understanding of problems and solutions related to information security and information assurance in organizational contexts. Students learn how to conduct quantitative and qualitative security risk assessment analyses related to site safety and security, hardware and software reliability and risks, and network reliability and security. Students will carry out data collection and analytics methodologies which address expected failures, incidence and severity of attacks, accidents and acts of nature, and their impacts on operations and budgets.
This course introduces students to modern machine-learning methods that can be applied to build predictive models & discover patterns in data for better-informed business decision-making. Students will learn implementation of the machine learning techniques in R programming language for understanding complex datasets. This course will enable students to approach business problems by identifying opportunities to derive business value from data-driven business intelligence. Prerequisites: QUMT 6303 or QUMT 3341 or equivalent
This course introduces the principles and techniques of prescriptive analytics. These provide business entities and policymakers with rational tools for evaluating performance, making decisions, designing strategies, and managing risk. Students will learn how to use analytical models to evaluate uncertainty that is prevalent in many business decisions. Since Business problems often have alternative solutions, students will learn how to use analytical models to assess various business solutions and identify the best course of action. This course involves a hands-on learning experience with spreadsheet modeling and other analytical packages. The emphasis is on how to employ these analytical methods to facilitate managerial decision-making in diverse industries and functional areas.

Calendar - Summer II Module

Course Start Date

Application Deadline

Payment Deadline

Registration Deadline

Course End Date

Tuition & Financial Aid

UT Rio Grande Valley's 100% online accelerated graduate programs offer affordable tuition, and financial aid is available for those who qualify.

Total Program Cost

Per Credit Hour

Per 3-Credit-Course

*We estimate that tuition and fees will total no more than the rates shown above; however, rates are subject to change.


For more information on our Graduate Scholarships, please visit our Scholarships page.

Financial Aid

UTRGV is an equal opportunity institution in the administration of its financial aid programs. In keeping with this policy, financial aid is extended to students without regard to race, creed, sex, national origin, veteran status, religion, age or disability. For additional information regarding funding please visit our Financial Aid for Accelerated Online Programs page.

Additional Fees

No Application Fee
Graduation Fee: $50


Please review all the admission requirements for the Master of Business Administration with a specialization in Business Analytics degree program. For specific questions or more details, contact an enrollment specialist at 1-833-887-4842.

Admissions Criteria

Online Application

Submit your application online.

Official Transcript

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3.0 (on a 4.0 scale)


Required for admission. GMAT/GRE waiver available