Doctor of Computer Science - Big Data Analytics Concentration
The Doctor of Computer Science with a concentration in Big Data Analytics (DCS-BDA) is a 100-credit-hour terminal degree in computer science. The program includes 40 credit hours of core management courses, 20 credit hours of big data analytics concentration courses, 4 credit hours of symposium-related courses, and 36 credit hours of doctoral research. The research element will culminate in a dissertation.
The DCS-BDA program is designed to aid leaders, data analysts, and data scientists in the development and use of tools and techniques to analyze large amounts of distributed, unstructured data in order to produce meaningful insight and automation for their respective organizations.
Doctor of Computer Science Outcomes
- Demonstrate fluency within the chosen discipline and the ability to support computer science strategy and technology in changing environments
- Develop synthesis proficiencies for strategic computer science solution generation in the context of internal and external technology adoption and application
- Integrate computer science theories, models, skills, and competencies in support of organizational missions
Big Data Analytics Concentration Outcomes
- Demonstrate an understanding of the common characteristics of big data: volume, velocity, variety, and veracity
- Assess and apply the use of big data software tools to organize various types of datasets
- Evaluate artificial intelligence solutions to big data problems
- Devise algorithms for efficiently processing big data to support business operations
- Create a big data use-and-analysis framework for the mission of an organization
Degree Requirements
Courses: Core
| CS814 | Current Topics in Computer Science and Information Systems | 4 |
| CS828 | Advanced Topics in Database Systems | 4 |
| CS844 | Concurrent and Distributed Systems | 4 |
| CS857 | Business Intelligence | 4 |
| CS871 | Advanced Quantitative Analysis | 4 |
| CS875 | Futuring and Innovation | 4 |
| CS877 | Introduction to Big Data Analytics | 4 |
| CS879 | Advanced Topics in Big Data Analytics | 4 |
| CS881 | Analytics for Big Data | 4 |
| CS882 | Tools for Big Data Analytics | 4 |
| | |
| RES804 | Principles of Research Methods and Design | 4 |
| RES812 | Qualitative Research Methods | 4 |
| RES814 | Quantitative Research Methods | 4 |
| RES860 | Doctoral Research I: Principles of Research and Writing | 4 |
| RES861 | Doctoral Research II: Annotated Bibliography | 4 |
| RES862 | Dissertation Research Process | 4 |
| RES863 | Doctoral Research III: Dissertation Literature Review | 4 |
| RES864 | Doctoral Research IV: Dissertation Methods | 4 |
| RES865 | Doctoral Research V: Dissertation Introduction | 4 |
| RES866 | Doctoral Research VI: Dissertation Findings | 4 |
| RES867 | Doctoral Research VII: Dissertation Discussion and Conclusion | 4 |
| RES868 | Doctoral Research VIII: Dissertation Conclusion | 4 |
| Electives | Select two 4- credit courses from 800-level CS or EM or EIS courses | 8 |
| SYMP801 | Doctoral Symposium I | 2 |
| SYMP802 | Doctoral Symposium II | 2 |
| Total Credit Hours: | 100 |
Electives: DCS students must complete two 4-credit courses for these electives. These courses may be selected from any of those offered under DCS. One of those electives may be chosen from the Doctor of Management program instead.
Total Credit Hours: 100
Program Areas of Focus
The DCS program is designed to provide candidates with theoretical, research, and application capabilities in the field. The areas of focus are described below.
Foundations
The program provides a focus on computer science and information systems topics and an orientation to research and writing at the doctoral level. Coursework covers current topics in the disciplines as well as research methods and qualitative techniques. The research component results in a broad overview of the student’s area of concentration in order to put the research into context and inform the student’s selection of a research topic.
Acquisition of Knowledge
Once the foundations are in place, the focus is on student development of an in-depth understanding of the knowledge and research methods in his or her chosen area of study. While most of the focus is on developing a richer understanding of the discipline, the research courses include quantitative methods and the dissertation process.
Leadership and Professional Advancement
The program includes the two remaining concentration courses plus the final six doctoral research courses that are designed to help students to complete the research and dissertation.
Symposium
Doctoral programs at Colorado Technical University require a residential symposium. Additional information about CTU's doctoral symposium can be viewed in the Doctoral Symposium section of this catalog.
Graduation Requirements
In addition to the successful completion of the above 100 credits with an acceptable GPA, students must also satisfactorily complete their research proposal and final dissertation. The research proposal must be approved by the student’s Research Supervisor and University Reviewer. The dissertation, which must be approved by the student’s dissertation committee, is an extensive document that includes the research study. In addition, graduation requires presentation of the final dissertation.
Locations
- Aurora (Denver Area)
- Virtual Campus
Area of Study
- Engineering & Computer Science