Master of Science (M.S.) Major in Data Analytics and Information Systems (Thesis Option)
Program Overview
The science of analyzing data to make actionable data-driven business decisions and gain competitive advantage has received widespread attention among business and government enterprises in the last few years. Variously referred to as Business Intelligence, Data Analytics, or Data Science, this is an emerging field that uniquely combines mathematical and statistical modeling, data visualization and information systems. The primary driving force behind the significant increase in the use of data analytics has been the extensive digitization of intra- and inter-organizational processes that generate massive amounts of data. This discipline has experienced an explosive growth during the past few years.
The main objective of the M.S. major in Data Analytics and Information Systems is to ensure that graduates can use appropriate data analysis methods and cutting-edge information technologies to derive actionable business intelligence. In a survey by KPMG, 99% of surveyed executives indicated that the skills for managing and analyzing big data sets to derive actionable insights is important for developing sound business strategy. This requires employees with advanced knowledge of data management technologies to manage big data sets and apply appropriate analytical techniques to analyze these data sets. The proposed program will provide students with integrated knowledge of information technology and data analysis methods to effectively manage and analyze data to support data-driven decision-making. The curriculum of the degree program will provide students with the technical skills required for the DSA jobs. This includes both information systems and data analytics skills such as data management, structured query language, R and Python programming, descriptive, predictive and prescriptive analytics, machine learning, statistical computing, big data analysis, and data visualization.
Application Requirements
The items listed below are required for admission consideration for applicable semesters of entry during the current academic year. Submission instructions, additional details, and changes to admission requirements for semesters other than the current academic year can be found on The Graduate College's website. International students should review the International Admission Documents page for additional requirements.
- completed online application
- $55 nonrefundable application fee
or
- $90 nonrefundable application fee for applications with international credentials
- baccalaureate degree from a regionally accredited university
- official transcripts from each institution where course credit was granted
- a competitive GPA in the last 60 hours of undergraduate course work (plus any completed graduate courses)
- official GMAT or GRE (general test only) with a competitive score
- responses to specific essay questions and a personal statement
- resume/CV detailing work experience, extracurricular and community activities, and honors and achievements
- three letters of recommendation from individuals best able to assess the student’s ability to succeed in graduate school
TOEFL, PTE, or IELTS Scores
-
Non-native English speakers who do not qualify for an English proficiency waiver:
- official TOEFL iBT scores required with a 78 overall and minimum individual module scores of
- 19 listening
- 19 reading
- 19 speaking
- 18 writing
- official PTE scores required with a 52
- official IELTS (academic) scores required with a 6.5 overall and minimum individual module scores of 6.0
This program does not offer admission if the scores above are not met.
Degree Requirements
The Master of Science (M.S.) degree with a major in Data Analytics and Information Systems requires 30 semester credit hours, including a thesis.
Any student enrolled in a graduate degree program in the McCoy College of Business Administration can earn no more than two grades of C or lower. Even if the grade of C or lower was replaced with a higher grade as a result of repeating the course, the original grade counts as a “strike” under this policy. Upon earning the third C (or lower), the student is automatically placed on academic suspension and permanently dismissed from their degree program without any possibility of readmission to their program or another degree program in McCoy College. The 3 C Policy takes precedent over probationary status. So, if a student earns a third C they are automatically dismissed from their program permanently; even if probation does not occur.
Course Requirements
| Code | Title | Hours |
|---|---|---|
| Required Courses | ||
| CIS 5355 | Database Management Systems | 3 |
| CIS 5357 | Computing for Data Analytics | 3 |
| CIS 5364 | Data Warehousing | 3 |
| CIS 5367 | Machine Learning | 3 |
| QMST 5332 | Optimization for Business Analytics | 3 |
| QMST 5334 | Statistical Methods for Business | 3 |
| QMST 5335 | Forecasting and Simulation | 3 |
| QMST 5336 | Analytics | 3 |
| Thesis Courses | ||
| CIS 5399A | Thesis | 3 |
| or QMST 5399A | Thesis | |
| Choose a minimum of 3 hours from the following: | 3 | |
| Thesis | ||
or QMST 5199B | Thesis | |
| Thesis | ||
or QMST 5299B | Thesis | |
| Thesis | ||
or QMST 5399B | Thesis | |
| Thesis | ||
or QMST 5599B | Thesis | |
| Thesis | ||
or QMST 5999B | Thesis | |
| Total Hours | 30 | |
Comprehensive Examination Requirement
All MSDAIS students are required to take a written comprehensive examination in their last semester of the program. Students must pass the comprehensive exam during the last semester in at most two attempts. If a student fails to pass the comprehensive exam in two attempts during the final semester, the student will retake the comprehensive exam during the next regular semester.
Students who do not successfully complete the requirements for the degree within the timelines specified will be dismissed from the program.
If a student elects to follow the thesis option for the degree, a committee to direct the written thesis will be established. The thesis must demonstrate the student’s capability for research and independent thought. Preparation of the thesis must be in conformity with the Graduate College Guide to Preparing and Submitting a Thesis or Dissertation.
Thesis Proposal
The student must submit an official Thesis Proposal Form and proposal to his or her thesis committee. Thesis proposals vary by department and discipline. Please see your department for proposal guidelines and requirements. After signing the form and obtaining committee members’ signatures, the graduate advisor’s signature if required by the program and the department chair’s signature, the student must submit the Thesis Proposal Form with one copy of the proposal attached to the dean of The Graduate College for approval before proceeding with research on the thesis. If the thesis research involves human subjects, the student must obtain exemption or approval from the Texas State Institutional Review Board prior to submitting the proposal form to The Graduate College. The IRB approval letter should be included with the proposal form. If the thesis research involves vertebrate animals, the proposal form must include the Texas State IACUC approval code. It is recommended that the thesis proposal form be submitted to the dean of The Graduate College by the end of the student’s enrollment in 5399A. Failure to submit the thesis proposal in a timely fashion may result in delayed graduation.
Thesis Committee
The thesis committee must be composed of a minimum of three approved graduate faculty members.
Thesis Enrollment and Credit
The completion of a minimum of six hours of thesis enrollment is required. For a student's initial thesis course enrollment, the student will need to register for thesis course number 5399A. After that, the student will enroll in thesis B courses, in each subsequent semester until the thesis is defended with the department and approved by The Graduate College. Preliminary discussions regarding the selection of a topic and assignment to a research supervisor will not require enrollment for the thesis course.
Students must be enrolled in thesis credits if they are receiving supervision and/or are using university resources related to their thesis work. The number of thesis credit hours students enroll in must reflect the amount of work being done on the thesis that semester. It is the responsibility of the committee chair to ensure that students are making adequate progress toward their degree throughout the thesis process. Failure to register for the thesis course during a term in which supervision is received may result in postponement of graduation. After initial enrollment in 5399A, the student will continue to enroll in a thesis B course as long as it takes to complete the thesis. Thesis projects are by definition original and individualized projects. As such, depending on the topic, methodology, and other factors, some projects may take longer than others to complete. If the thesis requires work beyond the minimum number of thesis credits needed for the degree, the student may enroll in additional thesis credits at the committee chair's discretion. In the rare case when a student has not previously enrolled in thesis and plans to work on and complete the thesis in one term, the student will enroll in both 5399A and 5399B.
The only grades assigned for thesis courses are PR (progress), CR (credit), W (withdrew), and F (failing). If acceptable progress is not being made in a thesis course, the instructor may issue a grade of F. If the student is making acceptable progress, a grade of PR is assigned until the thesis is completed. The minimum number of hours of thesis credit (“CR”) will be awarded only after the thesis has been both approved by The Graduate College and released to Alkek Library.
A student who has selected the thesis option must be registered for the thesis course during the term or Summer I (during the summer, the thesis course runs ten weeks for both sessions) in which the degree will be conferred.
Thesis Deadlines and Approval Process
Thesis deadlines are posted on The Graduate College website under "Current Students." The completed thesis must be submitted to the chair of the thesis committee on or before the deadlines listed on The Graduate College website.
The following must be submitted to The Graduate College by the thesis deadline listed on The Graduate College website:
- The Thesis Submission Approval Form bearing original (wet) and/or electronic signatures of the student and all committee members.
- One (1) PDF of the thesis in final form, approved by all committee members, uploaded in the online Vireo submission system.
After the dean of The Graduate College approves the thesis, Alkek Library will harvest the document from the Vireo submission system for publishing in the Digital Collections database (according to the student's embargo selection). NOTE: MFA Creative Writing theses will have a permanent embargo and will never be published to Digital Collections.
While original (wet) signatures are preferred, there may be situations as determined by the chair of the committee in which obtaining original signatures is inefficient or has the potential to delay the student's progress. In those situations, the following methods of signing are acceptable:
- signing and faxing the form
- signing, scanning, and emailing the form
- notifying the department in an email from their university's or institution's email account that the committee chair can sign the form on their behalf
- electronically signing the form using the university's licensed signature platform.
If this process results in more than one document with signatures, all documents need to be submitted to The Graduate College together.
No copies are required to be submitted to Alkek Library. However, the library will bind copies submitted that the student wants bound for personal use. Personal copies are not required to be printed on archival quality paper. The student will take the personal copies to Alkek Library and pay the binding fee for personal copies.
Master's level courses in Data Analytics and Information Systems: CIS, QMST
Courses Offered
Computer Information Systems (CIS):
CIS 5199B. Thesis.
This course represents a student's continuing thesis enrollment. The student continues to enroll in this course until the thesis is submitted for binding. Graded on a credit (CR), progress (PR), no-credit (F) basis.
1 Credit Hour. 1 Lecture Contact Hour. 0 Lab Contact Hours.Course Attribute(s): Exclude from 3-peat Processing
Grade Mode: Credit/No Credit
CIS 5299B. Thesis.
This course represents a student's continuing thesis enrollment. The student continues to enroll in this course until the thesis is submitted for binding. Graded on a credit (CR), progress (PR), no-credit (F) basis.
2 Credit Hours. 2 Lecture Contact Hours. 0 Lab Contact Hours.Course Attribute(s): Exclude from 3-peat Processing
Grade Mode: Credit/No Credit
CIS 5318. Information Technology in the Digital Economy.
Provides an understanding of the issues involved in the strategic management of the information assets of organizations. Examines the issues and challenges that users face within the Information Technology (IT) management arena as part of a firm’s business and IT strategy. Focus is on managerial rather than technical issues. Prerequisite: B A 5351 with a grade of "C" or better.
3 Credit Hours. 3 Lecture Contact Hours. 0 Lab Contact Hours.Grade Mode: Standard Letter
CIS 5355. Database Management Systems.
Explores the concepts, principles, issues and techniques for managing corporate data resources using database management systems. The course includes techniques for analysis, design and development of database systems, creating and using logical data models, database query languages, and procedures for evaluating database management software. Students will use a relational database management system to develop a management information system.
3 Credit Hours. 3 Lecture Contact Hours. 0 Lab Contact Hours.Grade Mode: Standard Letter
CIS 5356. Business Telecommunications.
Explores the technology that is revolutionizing the manner in which business and government conduct their operations and the effects new developments in communication media have on computing systems. This course reflects the current state-of-the-art in data communication networking.
3 Credit Hours. 3 Lecture Contact Hours. 0 Lab Contact Hours.Grade Mode: Standard Letter
CIS 5357. Computing for Data Analytics.
This course focuses on fundamentals of programming. Students will learn to design and implement applications, and programmatically handle a variety of data management functionalities.
3 Credit Hours. 3 Lecture Contact Hours. 0 Lab Contact Hours.Grade Mode: Standard Letter
CIS 5358. Agile Project Management For Business Professionals.
An in-depth study of the project management body of knowledge as applied to Information Technology with emphasis on Agile methodologies and the processes of managing scope, costs, schedules, quality and risks. Includes program management, system planning and design methodologies, material & capacity requirements, human, cultural, & international issues and their impact on the organization.
3 Credit Hours. 3 Lecture Contact Hours. 0 Lab Contact Hours.Grade Mode: Standard Letter
CIS 5360. E-Commerce: Strategies, Technologies, and Applications.
This course is designed to familiarize students with current and emerging e-commerce technologies. Topics include Internet technology for business advantage, reinventing the future of business through e-commerce, business opportunities in e-commerce, and social, political, global, and ethical issues associated with ecommerce.
3 Credit Hours. 3 Lecture Contact Hours. 0 Lab Contact Hours.Grade Mode: Standard Letter
CIS 5364. Data Warehousing.
Familiarizes students with current and emerging data warehousing technologies that play a strategic role in business organizations. Topics include data warehouse development life cycle, data warehouse navigation, data quality, and performance issues. Prerequisites: CIS 5355 with a grade of "C" or better.
3 Credit Hours. 3 Lecture Contact Hours. 0 Lab Contact Hours.Grade Mode: Standard Letter
CIS 5367. Machine Learning.
This course focuses on deriving actionable knowledge from data using algorithms and industry standard tools. It covers the complete process, key technologies, core machine learning algorithms, and programming used for business intelligence. Prerequisite: CIS 5357 and QMST 5336 both with grades of "C" or better.
3 Credit Hours. 3 Lecture Contact Hours. 0 Lab Contact Hours.Grade Mode: Standard Letter
CIS 5368. Information Security.
This course covers the analysis, design, development, implementation, and maintenance of information security systems in communication networks. Topics include legal, ethical, professional, and personnel issues; concepts, theories, and processes of risk management, technology; cryptography theory and practice; and physical and hardware security.
3 Credit Hours. 3 Lecture Contact Hours. 0 Lab Contact Hours.Grade Mode: Standard Letter
CIS 5369. Independent Study in Computer Information Systems.
This course focuses on individual in-depth research. Students, in consultation with a faculty member, choose a selected area of study in CIS and work independently on a specialized project. Course may be repeated with approval of department chair. Prerequisite: Instructor approval.
3 Credit Hours. 3 Lecture Contact Hours. 0 Lab Contact Hours.Course Attribute(s): Exclude from 3-peat Processing
Grade Mode: Standard Letter
CIS 5370. Enterprise Resource Planning and Business Intelligence.
The use of information technology in integrating enterprises for operational control and business intelligence is examined via Enterprise Resource Planning (ERP) applications in customer relationships management, accounting, finance, purchasing, production control, sales, marketing, and human resource management. Emphasizes managerial issues surrounding the need, selection, and implementation of ERP systems.
3 Credit Hours. 3 Lecture Contact Hours. 0 Lab Contact Hours.Grade Mode: Standard Letter
CIS 5371. Accounting Information Systems and Controls.
A study of accounting information systems and controls as well as their role in the current technology-intensive business environment. Emphasis is placed on contemporary technology and applications; information technology and business information systems assessments; design of internal controls to satisfy regulation and policy requirements; control concepts, theories, and processes; information systems auditing; systems development life cycle; and information structure, data transfer and transaction cycles. Prerequisite: ACC 3313 or ACC 5361 either with a grade of "C" or better.
3 Credit Hours. 3 Lecture Contact Hours. 0 Lab Contact Hours.Grade Mode: Standard Letter
CIS 5378. Information Security Policies and Compliance.
This course focuses on the technology and managerial issues related to information policies, regulations, and compliance that assure confidentiality, integrity, and availability of data and computer systems. Topics include information security policy, regulations, laws, standards, framework, compliance, and governance. Prerequisite: CIS 5368 with a grade of "C" or better.
3 Credit Hours. 3 Lecture Contact Hours. 0 Lab Contact Hours.Grade Mode: Standard Letter
CIS 5390C. Statistical Computing.
This course covers programming and statistical computing concepts. Programming concepts include data manipulation, data structures, control structures, functions, basic algorithms, and matrix manipulations. Statistical computing topics include numerical linear algebra, Monte Carlo methods, and numerical optimization.
3 Credit Hours. 3 Lecture Contact Hours. 0 Lab Contact Hours.Course Attribute(s): Exclude from 3-peat Processing|Topics
Grade Mode: Standard Letter
CIS 5390D. Introduction to Design Thinking.
This course provides an overview and hands on introduction to Design Thinking and the human centered design process. Topics include and introduction, defining the problem, ideation and concept generation, prototyping and testing and refining and launching.
3 Credit Hours. 3 Lecture Contact Hours. 0 Lab Contact Hours.Course Attribute(s): Exclude from 3-peat Processing|Topics
Grade Mode: Standard Letter
CIS 5395. Internship in Computer Information Systems.
This course provides students with opportunities for experiential learning by working on a computer information systems project. It enables integration of professional and academic experience through internship with an external employer. Prerequisite: Instructor approval.
3 Credit Hours. 1 Lecture Contact Hour. 20 Lab Contact Hours.Course Attribute(s): Exclude from 3-peat Processing
Grade Mode: Credit/No Credit
CIS 5399A. Thesis.
This course represents a student's initial thesis enrollment. No thesis credit is awarded until the student has completed the thesis in Data Analytics and Information Systems. Graded on a credit (CR), progress (PR), no-credit (F) basis.
3 Credit Hours. 3 Lecture Contact Hours. 0 Lab Contact Hours.Grade Mode: Credit/No Credit
CIS 5399B. Thesis.
This course represents a student's continuing thesis enrollment. The student continues to enroll in this course until the thesis is submitted for binding. Graded on a credit (CR), progress (PR), no-credit (F) basis.
3 Credit Hours. 3 Lecture Contact Hours. 0 Lab Contact Hours.Course Attribute(s): Exclude from 3-peat Processing
Grade Mode: Credit/No Credit
CIS 5599B. Thesis.
This course represents a student's continuing thesis enrollment. The student continues to enroll in this course until the thesis is submitted for binding. Graded on a credit (CR), progress (PR), no-credit (F) basis.
5 Credit Hours. 5 Lecture Contact Hours. 0 Lab Contact Hours.Course Attribute(s): Exclude from 3-peat Processing
Grade Mode: Credit/No Credit
CIS 5999B. Thesis.
This course represents a student's continuing thesis enrollment. The student continues to enroll in this course until the thesis is submitted for binding. Graded on a credit (CR), progress (PR), no-credit (F) basis.
9 Credit Hours. 9 Lecture Contact Hours. 0 Lab Contact Hours.Course Attribute(s): Exclude from 3-peat Processing
Grade Mode: Credit/No Credit
Quantitative Methods and Statistics (QMST):
QMST 5199B. Thesis.
This course represents a student's continuing thesis enrollment. The student continues to enroll in this course until the thesis is submitted for binding. Graded on a credit (CR), progress (PR), no-credit (F) basis.
1 Credit Hour. 1 Lecture Contact Hour. 0 Lab Contact Hours.Course Attribute(s): Exclude from 3-peat Processing
Grade Mode: Credit/No Credit
QMST 5299B. Thesis.
This course represents a student's continuing thesis enrollment. The student continues to enroll in this course until the thesis is submitted for binding. Graded on a credit (CR), progress (PR), no-credit (F) basis.
2 Credit Hours. 2 Lecture Contact Hours. 0 Lab Contact Hours.Course Attribute(s): Exclude from 3-peat Processing
Grade Mode: Credit/No Credit
QMST 5332. Optimization for Business Analytics.
This course introduces optimization theory and applications for analyzing and solving business decision-making problems. The students will learn to apply in various business domains optimization concepts and tools such as linear programming, integer/mixed-integer programming, and other classes of optimization models.
3 Credit Hours. 3 Lecture Contact Hours. 0 Lab Contact Hours.Grade Mode: Standard Letter
QMST 5334. Statistical Methods for Business.
The course provides the quantitative foundation for business analysis and decision making. Topics include: inferential statistics, regression analysis, and other analytical/modeling techniques with wide applicability in decision-making and problem solving in all functional areas of business.
3 Credit Hours. 3 Lecture Contact Hours. 0 Lab Contact Hours.Grade Mode: Standard Letter
QMST 5335. Forecasting and Simulation.
This course introduces the concepts and principles of forecasting and simulation techniques as applies to planning and decision making in organizations. Topical coverage includes time series forecasting, casual forecasting, discrete event simulation, and continues-event simulation techniques.
3 Credit Hours. 3 Lecture Contact Hours. 0 Lab Contact Hours.Grade Mode: Standard Letter
QMST 5336. Analytics.
This course introduces analytics which refers to the process of transforming data into information for making decisions. The topics include the introduction to analytics, visualization, analytics applications, and challenges related to business data. Students will learn how to use software, conduct data analysis and communicate their results.
3 Credit Hours. 3 Lecture Contact Hours. 0 Lab Contact Hours.Grade Mode: Standard Letter
QMST 5338. Operations Management.
This course introduces the processes and strategies to create, produce, and deliver goods and services that drive organizations’ overall success. It will highlight operational and tactical problems organizations typically confront and introduce the concepts and analytical tools (both process and systems based) used to deal with these problems. Prerequisite: QMST 5334 with a grade of "C" or better.
3 Credit Hours. 3 Lecture Contact Hours. 0 Lab Contact Hours.Grade Mode: Standard Letter
QMST 5342. Probability and Statistical Models.
This course introduces the concept of probability and probability distributions. It includes general and generalized linear models, inflated and mixture models, and hierarchical models. Model validity and choice will also be discussed.
3 Credit Hours. 3 Lecture Contact Hours. 0 Lab Contact Hours.Grade Mode: Standard Letter
QMST 5343. Data Mining.
This course covers data mining concepts and applications of data mining techniques to solve business problems. It emphasizes algorithms such as classification, clustering, association, and text mining. Model selection and assessment are also emphasized. Prerequisite: QMST 5336 with a grade of "C" or better.
3 Credit Hours. 3 Lecture Contact Hours. 0 Lab Contact Hours.Grade Mode: Standard Letter
QMST 5369. Independent Study in Quantitative Methods.
This course focuses on individual in-depth research. Students, in consultation with a faculty member, choose a selected area of study in quantitative methods and work independently on a specialized project. Course may be repeated with approval of department chair. Prerequisite: Instructor approval.
3 Credit Hours. 3 Lecture Contact Hours. 0 Lab Contact Hours.Course Attribute(s): Exclude from 3-peat Processing
Grade Mode: Standard Letter
QMST 5390A. Statistical Computing.
This course covers programming and statistical computing concepts. Programming concepts include data manipulation, data structures, control structures, functions, basic algorithms, and matrix manipulations. Statistical computing topics include numerical linear algebra, Monte Carlo methods, and numerical optimization.
3 Credit Hours. 3 Lecture Contact Hours. 0 Lab Contact Hours.Course Attribute(s): Exclude from 3-peat Processing|Topics
Grade Mode: Standard Letter
QMST 5395. Internship in Analytics.
This course is based on experiential learning while the student works in quantitative methods and statistics. Students will integrate both professional and academic experiences through the internship with an external employer. Prerequisite: Instructor approval.
3 Credit Hours. 1 Lecture Contact Hour. 20 Lab Contact Hours.Course Attribute(s): Exclude from 3-peat Processing
Grade Mode: Standard Letter
QMST 5399A. Thesis.
This course represents a student's initial thesis enrollment. No thesis credit is awarded until the student has completed the thesis in Data Analytics and Information Systems. Graded on a credit (CR), progress (PR), no-credit (F) basis.
3 Credit Hours. 3 Lecture Contact Hours. 0 Lab Contact Hours.Grade Mode: Credit/No Credit
QMST 5399B. Thesis.
This course represents a student's continuing thesis enrollment. The student continues to enroll in this course until the thesis is submitted for binding. Graded on a credit (CR), progress (PR), no-credit (F) basis.
3 Credit Hours. 3 Lecture Contact Hours. 0 Lab Contact Hours.Course Attribute(s): Exclude from 3-peat Processing
Grade Mode: Credit/No Credit
QMST 5599B. Thesis.
This course represents a student's continuing thesis enrollment. The student continues to enroll in this course until the thesis is submitted for binding. Graded on a credit (CR), progress (PR), no-credit (F) basis.
5 Credit Hours. 5 Lecture Contact Hours. 0 Lab Contact Hours.Course Attribute(s): Exclude from 3-peat Processing
Grade Mode: Credit/No Credit
QMST 5999B. Thesis.
This course represents a student's continuing thesis enrollment. The student continues to enroll in this course until the thesis is submitted for binding. Graded on a credit (CR), progress (PR), no-credit (F) basis.
9 Credit Hours. 9 Lecture Contact Hours. 0 Lab Contact Hours.Course Attribute(s): Exclude from 3-peat Processing
Grade Mode: Credit/No Credit
