Data Analytics

The name of the Department of Management Information Systems has been changed to Department of Computer Information Systems and Analytics effective July 1, 2021. Courses with the MIS subject prefix will catch up with that change by moving to the CISA subject prefix with the 2022–2023 Graduate Bulletin.

[1] Objectives

There are two graduate programs available in data analytics, the Graduate Certificate in Data Analytics (GC-DA) and the MS in Applied Data Analytics. Both of these programs prepare graduates for employment in managing, using and exploiting data in organizations to enhance decision-making. These programs are particularly useful for individuals who wish to shift careers or add to their repertoire of current skills. Such skills are useful in almost every area of business, including accounting, management, marketing, finance, etc. The effective management of data has become increasingly important in organizations, as companies gather more and more data and use it for strategic purposes. Using this data for better decision-making remains a primary goal of data analytics. Effectively using data requires expertise in a number of areas, including data management and cleansing, descriptive/predictive/prescriptive analytics, advanced statistics, and data mining, to name a few. While in small organizations, an analyst may need skills in many areas, in larger companies’ employees typically focus in particular areas.

The Graduate Certificate and MS in Applied Data Analytics provide a solid foundation for work in the technical field of analytics. The Masters degree provides foundational work in all the common skill areas of data analytics, while the Graduate Certificate focuses on select areas, depending on which electives are chosen. Either degree is useful for providing the skills necessary for work, though the MS degree provides more employment choices for students, given that it includes skills in many areas of analytics.

[2] Admission Requirements

In addition to the Graduate School admission requirements, a student may be admitted to either the MS in Applied Data Analytics or the GC in Data Analytics program by fulfilling the following requirements:

1. A bachelor’s degree from an accredited institution
2. An undergraduate cumulative GPA of at least 2.70, or 3.00 in last 60 credit hours.
3. A minimum 3.00 GPA on any graduate work (from anywhere)
4. A current professional résumé that specifies the applicant’s professional experience in business
5. College credit for a statistics (or business statistics) course

Note: The Graduate Certificate in Data Analytics requires its own application for admission. It may, however, also be completed in conjunction with either the MBA or MAcc. Both of these programs have elective hours that may be used to complete the GC-DA. See the information provided in Graduate Bulletin for either the MBA or MAcc for further information on completing the certificate while enrolled in one of these degree programs. The MS in Applied Data Analytics is a stand-alone program. A student with a previously awarded Graduate Certificate in Data Analytics may pursue the MS in Applied Data Analytics by completing the remaining degree requirements.

[3] Program Requirements

[3.1] Graduate Certificate in Data Analytics

To earn the GC in Data Analytics, the student must complete twelve (12) hours of graduate-level course work, as specified below. A cumulative GPA of 3.0 is required.

Prerequisite Course (3 credit hours)

Take the following two courses (6 hours)

Take two of the following five courses (6 hours)

[3.2] Master of Science in Applied Data Analytics

The MS in Applied Data Analytics requires 30 semester hours of graduate work, including a core of 24 hours, plus an additional 6 hours of electives.

Prerequisite Course (3 credit hours)

Required Courses (24 credit hours)

Electives: take two of the following (6 credit hours)

[4] Course Links

Follow this link for MIS course descriptions: course link.
Follow this link to the Undergraduate Bulletin for QMTH course description: course link.