Program Overview

Today more and more opportunities in the rapidly expanding field of business Analytics are becoming available for IT professionals. While basic IT managerial skills are very useful in this area, there are also special considerations of which IT professionals must be aware to make them effective in managing the data Analytics and big data needs of organizations. For effective and efficient management of the huge volumes of data and information being created every day, more and more organizations need the disciplines involved in business intelligence as manifested in the relatively new sub‐fields of Business Analytics and Predictive Analytics.

Upon completion of the Business Analytics Certificate, students will know basic information management, process analysis, and important general MIS/IT principles and practices (including security and information assurance). So, this Certificate will help students prepare for the exciting fields related to Business Analytics, and give them a real advantage for working in this rapidly growing field.

More information about this program

Gainful Employment Disclosure

Gainful employment programs are those "that prepare students for gainful employment in a recognized occupation." Public institutions are required to report this information for all undergraduate and graduate programs that are Title IV eligible and that lead to certificates, diplomas, graduate certificates or specialist awards. Degree programs at all levels are not considered to be gainful employment programs.

Gainful Employement Disclosure

Admission Criteria

Admission Decisions/Categories

The College of Management Graduate Admissions Committee evaluates your application for evidence of undergraduate scholarship, professional experience and demonstrated aptitude for successful graduate business study. If you meet all application requirements, you are given full admission to the program. If you have one or more prerequisite courses to complete and your application otherwise supports the conclusion that you can successfully undertake graduate study, you may be granted conditional admission to a program. As a conditionally-admitted student, you must complete these prerequisites prior to completing any graduate course work. Applicants denied admission may not take graduate level courses in the program.

Registration by Undergraduate Students

With permission of the MMIS Director, you may register for "special" graduate level prerequisite courses during your last semester of undergraduate studies.

Reapplication for Denied Applicants

If your application for admission to the program is denied, you may reapply for admission only after a minimum of six months has passed after the denial. You will need to demonstrate a substantive difference in the reapplication to be considered for admission.

If your application to the program is denied, you may apply for another College of Management graduate program. A new application form must be accompanied by the application fee, a new goals essay, updated resume, two new references and GMAT scores and/or assessment test scores appropriate to the degree for which you are applying.

English and Quantitative Competence Assessment

All College of Management students, except those in special international cohort programs, are expected to demonstrate English and quantitative competence at a level to support success in graduate studies. If your abilities are assessed to be inadequate for graduate study, you may be required to enroll in appropriate undergraduate courses until your skills have been brought to a satisfactory level. These undergraduate courses must be successfully completed prior to taking any graduate level courses.

COM Graduate Student Orientation

Once you are fully admitted to a College of Management graduate program you will be required to attend a graduate student orientation session before or during your first semester of course work. If you do not attend an orientation session, a hold will be placed on your records preventing you from registering for further graduate classes until you attend orientation.

Application Requirements

Applicants should allow 7-10 business days for review once all required application materials are received and sent to the College of Management Graduate Admissions Committee.
To be considered for admission you must submit:

  • Application
  • Non-refundable application fee
  • Official transcripts
  • Test scores
  • Current resume
  • Goals essay
  • References

See Applying to the Program for application packets, details on the requirements, deadlines and International Student application requirements.

Transfer Credits

Once fully admitted, you may transfer up to 8 credits into your graduate program. A course is accepted in transfer only if it has been completed within the last five years from an accredited institution, no degree was granted, and a letter grade of B or better was earned in the course. Courses are accepted in transfer only upon the approval of the Graduate Programs Director in consultation with discipline coordinators.

Additional Information

MIS Graduate Business Analytics Certificate:

Required Courses: (16 credits)

MIS 600 Management Information Systems (4 credits)
MIS 671 Problem Formulation, Data Presentation (4 credits)
MIS 687 Business Analytics (4 credits)
MIS 688 Predictive Analytics (4 credits) 

Electives: (4 credits of the following)

MIS 693 (Adv. Supply Chain Information Systems) (4 credits)

- OR

MIS 685 (Data Warehousing) (2 credits)
- AND -
MIS 686 (Adv. Data warehousing) (2 credits)

Total: (20 credits)

How Admissions Works

We are looking forward to you joining us. Take the first step by filling out this application.
Course List


  • Please verify that your Course List is separated by ',' (comma) or 'OR'

Requirements ( 20 total credits)

Required Courses (16 credits)

  • MIS 600 Management Information Systems
    4 credits

    Management Information Systems (MIS) evolved from essentially an organization's support operation to a strategic element of an organization's life and survival. This course explores information systems' new and expanding roles in the enterprise. Models examined showing how new technologies are assimilated into the organization, how to plan for systems within the overall strategic management process, assess the risk in system development projects, and become a "sophisticated user" of information systems. Traditional and new technologies are utilized. The course also includes a solid review of the strategic and tactical impact of computers, networks and new technologies. . This course broadens understanding of the design and implementation of various computerized information systems to support management decision making and evaluation, and prepares the student to integrate new technologies and configurations into the management process.

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  • MIS 671 Problem Formulation and Data Presentation
    4 credits

    This course provides students with techniques and strategies to work on complex business problems while exercising strong critical thinking skills. It also helps them develop potential solutions. This course then focuses on how to take the results of students' professional work and present complex material in a manner that helps them clearly explain and market their information.

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  • MIS 687 Business Analytics
    4 credits

    The improvement in computing and information management technology created opportunity for organizations to generate, store, and process huge amount of data which is being generated in every seconds. Business Analytics provides organizations a new, efficient way to intelligently use those data by combining it with sophisticated analytics. With Business Analytics, organizations can take advantage of data with leveraging and turning it into actionable intelligence that can be used to support reasoned decisions. This course is designed to provide an introduction to the concepts of Business Analytics and its applicability with real world data in a business environment. Students will gain experience using several cutting-edge software in Business Analytics to support business decision making. Students will also be familiarized with the overall life cycle of Business Analytics project (identify the problem, describe the data, analyze the data, interpret the results, and make recommendations) through three different modules: ¿ Module 1 - Business Analytics Fundamentals: Concepts ¿ Module 2 - Business Analytics Fundamentals: Basic predictive analytics ¿ Module 3 - Business Analytics in Actions: Applications, and practical insight

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  • MIS 688 Predictive Analytics
    4 credits

    Currently, enterprises across almost every industry are seeking talent for predictive analytics. Predictive analytics helps connect data to effective action by drawing reliable conclusions about current conditions and future events. Coupled with other types of analytics available (i.e., Descriptive, Diagnostic, and Prescriptive analytics), enterprises can make predictions and then proactively act upon that insight to drive better business outcomes and achieve measurable competitive advantage. Naturally, such demand is met with creative and critical thinking professionals that have been prepared with theories that can be put into practice. The Predictive Analytics course offering includes modules, activities and projects that are structured for following topic objectives: ¿ Understanding the different purposes of analytics (i.e., Diagnostics analytics for data discovery ¿ Why did it happen?, Predictive analytics for forecasting, and simulation ¿ What will happen?, and Prescriptive analytics for planning, and optimization ¿ What should we do?) to choose appropriate analytic techniques for decision making. ¿ Teaching the skills needed to understand the integration of resources (i.e. people, processes, technologies and facilities) to decision making based on predictable data patterns and trends. ¿ Building the skills to apply business intelligence, machine learning, decision science, knowledge discovery, and business performance management to obtain business insight that is linkage to foresight. ¿ Development of knowledge to broker content from multiple sources and systems, integrate into a common vocabulary that is universally meaningful for enterprise economic growth.

    Course Outline Class Schedule <<<<<<< HEAD ======= >>>>>>> 35179410ff55d83bece68cc1d84aadaa0fa744b8

Electives (4 credits)

  • One of the following classes is required:
    • MIS 686 Advanced Data Mining Tools
      2 credits

      The course gives students an opportunity to start with several Business Problems which require Data Mining techniques like classification, estimation, clustering. Students are supposed to research on Data Mining vendors/tools to find Strengths & Weaknesses for selected Data Mining tools Students are supposed to use 5 groups of Data Mining tools selection criteria: Hardware/OS/Networking, Data reparation/Manipulation, User Interface/Model Output, Algorithms & Manageability, Support/Documentation/Training. The course gives students an opportunity to exercise advanced Data Exploration and Mining software (developed by Synera Systems, Inc.) to analyze Retail Customer Behavior. Students are supposed to use a macro language to document Data Quality problems. Introduction to E-Customer Behavior is also a part of this course.

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    • MIS 693 Advanced Supply Chain Information Systems
      2 credits

      Beginning where MIS653/Mktg 653 Supply Chain Management/ Logistics Management leaves off, this course examines the use of information technology to improve efficiency and effectiveness in the corporate supply chain. Topics covered include the strategic role of key information technologies in business-to-business e-commerce; efficient customer response; enterprise resource planning; the virtual value chain. Prerequisite: MIS 653 Supply Chain Management/Logistics Management.

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  • MIS 685 Data Mining Tools
    2 credits

    This course introduces how analytics and Data Mining tools can be used to solve business problems like Best Next Offer, Customer Retention, Customer Potential Life Time Value estimation, Market Basket analysis, etc. This course gives students an opportunity to exercise advanced Data Exploration and Mining software. Introduction to Data Mining tools/solutions evaluation is also part of this course.

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