Data Analytics

Program Contacts

Jeff Hill, PhD: Department Chair and Graduate Program Coordinator
Telephone: (501) 450-5327 | Email: ghill@uca.edu

[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 (MS-ADA). 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

[2.1] Graduate Certificate in Data Analytics

Applicants not meeting the following requirements may be considered for conditional admission to the GC in Data Analytics program on a case-by-case basis.

In addition to the Graduate School admission requirements, an applicant will be considered for regular admission to the GC in Data Analytics program by fulfilling the following requirements:

  1. A bachelor’s degree from an accredited* institution
  2. College credit for a statistics (or business statistics) course
  3. Meet at least one (1) of the following criteria:
    1. Undergraduate cumulative GPA from an accredited* program or institution of at least 3.00, or 3.20 in the last 60 credit hours
    2. Taken the Graduate Management Admission Test (GMAT) or the Graduate Record Examination (GRE) earning scores in the 50th percentile or higher for the Verbal, Quantitative, and Analytical Writing sections of either exam
    3. Two (2) or more years of relevant, full-time employment
  4. Minimum 3.00 GPA on any graduate work (from anywhere)
  5. A current professional résumé that specifies the applicant’s relevant, full-time employment
  6. A one or two page cover letter highlighting the applicant’s experiences that have prepared them for graduate studies and how this credential will help them to achieve their career objectives

* “Accredited” may refer to business programs accredited by AACSB or EQUIS or institutions accredited by an institutional accreditor recognized by the U.S. Department of Education (or other appropriate accrediting agency as determined by the UCA Graduate School and the MS-ADA and GC-DA Program Coordinator).

[2.2] Master of Science in Applied Data Analytics

Applicants not meeting the following requirements may be considered for conditional admission to the MS in Applied Data Analytics program on a case-by-case basis. In addition to the Graduate School admission requirements, an applicant will be considered for full admission to the MS in Applied Data Analytics program by fulfilling the following requirements.

  1. A bachelor’s degree from an accredited* institution
  2. College credit for a statistics (or business statistics) courses
  3. Meet at least two (2) of the following criteria:
    1. Undergraduate cumulative GPA from an accredited* program or institution of at least 3.00, or 3.20 in the last 60 credit hours
    2. Taken the Graduate Management Test (GMAT) or the Graduate Record Examination (GRE), earning scores in the 50th percentile or higher for the Verbal, Quantitative, and Analytical Writing sections for either exam
    3. Two (2) or more years of relevant, full-time employment
    4. Successful completion of UCA’s Graduate Certificate in Data Analytics
  4. Minimum 3.00 GPA on any graduate work (from anywhere)
  5. An unimpeachable record of academic integrity
  6. A letter of recommendation from a faculty member from the most recent program of study
  7. A current professional résumé that specifies the applicant’s relevant, full-time employment
  8. A one- or two-page cover letter highlighting the applicant’s experiences that have prepared them for graduate studies and how this credential will help them achieve their career objectives

* “Accredited” may refer to business programs accredited by AACSB or EQUIS or institutions accredited by an institutional accreditor recognized by the U.S. Department of Education (or other appropriate accrediting agency as determined by the UCA Graduate School and the MS-ADA and GC-DA Program Coordinator).

[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)

CISA (formerly QMTH) 2330 Business Statistics [ACTS: BUSI2103] or equivalent

Take the following two courses (6 hours)

CISA 5380 Business Intelligence and Data Visualization
CISA 5381 Data Mining and Applied Analytics

Take two of the following six courses (6 hours)

CISA 5320 Critical Thinking and Experimental Design
CISA 5330 Prescriptive Analytics
CISA 6325 Predictive Analytics
CISA 6335 Python for Data Analytics
CISA 6365 Data Management
CISA 6V71 Special Topics in Data Analytics

[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)

CISA (formerly QMTH) 2330 Business Statistics [ACTS: BUSI2103] or equivalent

Required Courses (24 credit hours)

CISA 5320 Critical Thinking and Experimental Design
CISA 5330 Prescriptive Analytics
CISA 5380 Business Intelligence and Data Visualization
CISA 5381 Data Mining and Applied Analytics
CISA 6325 Predictive Analytics
CISA 6335 Python for Data Analytics
CISA 6365 Data Management
CISA 6370 Applied Data Analytics Project

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

MBA 6301 Information Technology for Managers
ACCT 6320 Seminar in Accounting Information Systems
CISA 5355 Project Management Leadership
CISA 6355 Information Technology Project Management
CISA 6V71 Special Topics in Data Analytics
CISA 6V82 Internship in Data Analytics

[4] Course Links

Follow this link for CISA course descriptions: course link.