Business Analytics (Certificate)

Business Analytics (Certificate)

Apply Now Print Page

DATA-DRIVEN DECISIONS

Business decisions in the 21st century are increasingly dependent on smart analytics which extract and apply the value inherent in data. Using current powerful data analytics tools and methods, students in this program learn how to select, collect and analyze information, and effectively communicate results.

STEP UP TO SUCCESS

Students who complete the 12 hours (4 courses) required for the graduate certificate may wish to continue on to a full MBA degree, in which 9 hours of analytics courses constitutes a concentration in Business Analytics for their MBA. Continue to watch this space in the future for additional course topics, and new degree programs for Business Analytics! 

  • Admission Requirements

    Step #1: Submit a UTRGV Graduate Application at www.utrgv.edu/gradapply. There is no application fee.

    Step #2: Request your official transcripts to be sent electronically to gradapps@utrgv.edu or mailed to:

    The University of Texas Rio Grande Valley
    The Graduate College
    Marialice Shary Shivers Bldg. 1.158
    1201 W. University Drive
    Edinburg, TX 78539-2999

     
    *Please Note: If you are a graduate of UTPA, UTB/TSC, or UTRGV you do not need to request an official transcript to be sent to the Graduate College.

    Review and submit all Program Requirements:

    • Bachelor's degree from a regionally accredited institution in the United States or a recognized international equivalent in a similar or related field.
    • Official transcripts from each institution attended (must be submitted directly to UTRGV).
    • Undergraduate GPA of at least 3.0. If applicant does not meet minimum undergraduate GPA criterion, GRE general test with minimum scores of 150 Verbal, 141 Quantitative, and 4.0 Analytical are required for conditional admission.

    Students whose native  language is not English  or  who studied at a University outside the U.S.:

    • TOEFL or IELTS Language Proficiency Test with minimum scores: 550 on paper-based, 213 on computer based, or 79 on Internet-based for the TOEFL; 6.5 for the IELTS. TOEFL and IELTS scores are valid for 2 years. For additional information, visit the English Proficiency Exam section of our website.
    • Certified English translation of educational records.

     

  • Program Contact

    Program Coordinator: Dr. Jerald Hughes

    Phone: 956-665-7317

    Office: Edinburg Campus, EMAGC 3114

    E-Mail: j.hughes@utrgv.edu

  • Deadlines

    Deadlines:

    Applications will be accepted year round and prospective students are encouraged to apply at least 2 months before classes start to ensure a timely application review.  Applying early will also give prospective students the best opportunity to be considered for scholarships and other possible funding opportunities.

    *Note:

    • This program only admits applicants during Fall, Spring, Summer I & Summer II semesters.
    • Students admitted only to a Certificate Program are not eligible to obtain a Student Visa from UTRGV.
  • Tuition Estimate

    Residency Per 3-Credit Hour Course Semester (9-Credit Hours) Total Estimated Cost
    Texas Resident $1,359.29 $3,563.87 $4,666.16
    Non-Resident/International $2,625.29 $7,361.87 $9,730.16


    *We estimate that tuition and fees will closely approximate the rates shown above; however, rates are subject to change. Please note that the rates above are estimated for on-campus students and those enrolled in 16-week online programs. The rate is different for Accelerated Online Programs (AOP). Visit the tuition and fees page for detailed information.

  • Course Requirements

     
    Required Courses 12
    INFS 6340: Health Computer Information Systems   3
    INFS 6343: Healthcare Analytics   3
    INFS 6350: Foundations of Business Analytics   3
    INFS 6351: Application Development for Business Analytics   3
    INFS 6353: Social Media Analytics   3
    INFS 6356: Data Wareshousing and Visualization   3
    INFS 6359: Data Mining for Business Analytics   3
    INFS 6363: Enterprise Analytics   3
    INFS 6391: Information Security and Assurance Management   3
    QUMT 6303: Statistical Foundations   3
    QUMT 6350: Decision Modeling for Business Analytics   3
    QUMT 6360: Decision Optimization for Business Analytics   3
    Total hours required for completion  12

     

    Course Descriptions

    INFS 6340: Health Computer Information Systems                                                                     [3-0]

    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.

    INFS 6343: Healthcare Analytics                                                                     [3-0]

    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 healht. 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.

    INFS 6350: Foundations of Business Analytics                                                                     [3-0]

    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.

    INFS 6351: Application Development for Business Analytics                                                 [3-0]

    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.

    Prerequisite: QUMT 6303 or QUMT 3341 or equivalent. 

    INFS 6353: Social Media Analytics                                                                     [3-0]

    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.

    INFS 6356: Data Warehousing and Visualization                                                                     [3-0]

    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.

    INFS 6359: Data Mining for Business Analytics                                                                     [3-0]

    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.

    Prerequisite: QUMT 6303 or QUMT 3341 or equivalent.

    INFS 6363: Enterprise Analytics                                                                     [3-0]

    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.

    INFS 6391: Information Security and Assurance Management                                                                     [3-0]

    This course is targeted towards graduate students and practitioners as it focuses on the significance of Information Security in present-day business organizations. The objective of this course is to provide students with a comprehensive understanding of the problems related to Information Security, and solutions to these problems. Students will receive theoretical and practical instructions in both managerial and technical aspects of securing information in organizations. The course will be helpful to students who are interested in attaining Certified Information Systems Security Professional certification and/or careers in Information Security.

     QUMT 6303: Statistical Foundations                                                           [3-0]

    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.

     QUMT 6350: Decision Modeling for Business Analytics                                                           [3-0]

    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.

     QUMT 6360: Decision Optimization for Business Analytics                                                           [3-0]

    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.

     

program page footer