Master of Business Administration with a specialization in Business Analytics

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. Apply Now Continue Your Application
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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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Courses

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
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 studies.
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.
The study of advanced topics and cases in corporate managerial finance. The course builds on the foundation finance course; and covers topics including valuation of securities, valuation of 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.
This course is an advanced study of marketing policy and decision-making based upon a consumer orientation, innovation and creative adaptation to change, cultural implication of marketing action, 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.
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.
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 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.
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
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 studies.
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.
The study of advanced topics and cases in corporate managerial finance. The course builds on the foundation finance course; and covers topics including valuation of securities, valuation of 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.
This course is an advanced study of marketing policy and decision-making based upon a consumer orientation, innovation and creative adaptation to change, cultural implication of marketing action, 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.
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.
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 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.
This course discusses the process of business analytics based on data modeling including problem definition, data preparation, descriptive and predictive analyses, evaluation of results, implementation and deployment. Data oriented methods using spreadsheet and structured query language (SQL) are emphasized for business transaction capturing, data aggregation and online analytic processing (OLAP). Students will perform analyses with various software packages in business contexts.
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 introduces concepts, techniques, and tools for managing and understanding data in healthcare. The course focuses on teaching students to use healthcare data to make decisions, transform health care delivery, and improve public health. Students will learn how to collect, process, analyze, visualize, and report structured and unstructured clinical and operational data. Topics covered include healthcare data measurement, statistical analysis, and data mining. This course will discuss challenges related to healthcare analytics such as data privacy, security, and interoperability.
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, actions, hyperlinks, mobile, location and search engine data. Students will learn how businesses align social media analytics with their business strategies and gain insights on trends and user behaviors. An emphasis is placed on using various software tools to analyze real-world social media data.
This course focuses on realizing the business advantage of utilizing data to support managerial decisions. Students will employ a variety of software tools in the development of data warehouse, including ETL (extraction, transformation and loading), and visual data representations (e.g. dashboards, data cubes). Hands-on exercises include dimensional modeling, MS-Excel, and Tableau, among others.
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 various prescriptive analytic techniques and tools that can be used to analyze business decision problems and create business value. Topics may include deploy analytics such as aggregate planning models and complex problem solving. Analytical packages and modeling software such as Excel solver for linear and integer programming will be extensively used throughout the course. The emphasis of this course will be placed on the application of techniques and interpretation of the results.
This course introduces the principles and techniques of prescriptive analytics. These provide business entities and policy makers 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, studnets will learn how to use analytical models to assess various business solutions and identify the best course of action. Tjis 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.
This course discusses the process of business analytics based on data modeling including problem definition, data preparation, descriptive and predictive analyses, evaluation of results, implementation and deployment. Data oriented methods using spreadsheet and structured query language (SQL) are emphasized for business transaction capturing, data aggregation and online analytic processing (OLAP). Students will perform analyses with various software packages in business contexts.
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 introduces concepts, techniques, and tools for managing and understanding data in healthcare. The course focuses on teaching students to use healthcare data to make decisions, transform health care delivery, and improve public health. Students will learn how to collect, process, analyze, visualize, and report structured and unstructured clinical and operational data. Topics covered include healthcare data measurement, statistical analysis, and data mining. This course will discuss challenges related to healthcare analytics such as data privacy, security, and interoperability.
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, actions, hyperlinks, mobile, location and search engine data. Students will learn how businesses align social media analytics with their business strategies and gain insights on trends and user behaviors. An emphasis is placed on using various software tools to analyze real-world social media data.
This course focuses on realizing the business advantage of utilizing data to support managerial decisions. Students will employ a variety of software tools in the development of data warehouse, including ETL (extraction, transformation and loading), and visual data representations (e.g. dashboards, data cubes). Hands-on exercises include dimensional modeling, MS-Excel, and Tableau, among others.
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 various prescriptive analytic techniques and tools that can be used to analyze business decision problems and create business value. Topics may include deploy analytics such as aggregate planning models and complex problem solving. Analytical packages and modeling software such as Excel solver for linear and integer programming will be extensively used throughout the course. The emphasis of this course will be placed on the application of techniques and interpretation of the results.
This course introduces the principles and techniques of prescriptive analytics. These provide business entities and policy makers 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, studnets will learn how to use analytical models to assess various business solutions and identify the best course of action. Tjis 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.
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 examination of financial and managerial accounting theory and concepts and their application in financial and managerial decision making.
An introduction to statistical methodology to include probability concepts, inference techniques, analysis of variance, regression analysis, chi square and other nonparametric analyses. This course focuses on the use of the computer in performing statistical analysis.
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 examination of financial and managerial accounting theory and concepts and their application in financial and managerial decision making.
An introduction to statistical methodology to include probability concepts, inference techniques, analysis of variance, regression analysis, chi square and other nonparametric analyses. This course focuses on the use of the computer in performing statistical analysis.

Calendar

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Application Priority Deadline

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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.

Scholarships

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


Admissions

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

Submit transcripts from all colleges/universities

GPA

3.0 (on a 4.0 scale)

GMAT or GRE

Required for admission. GMAT/GRE waiver available