The request to revise Data Science and Business Analytics catalog copy and create DSBA cross-listings for all data science courses
Date: March 25, 2016
To: Belk College of Business
To: College of Computing & Informatics
From: Office of Academic Affairs
Approved On: March 7, 2016
Approved by: Graduate Council
Implementation Date: Fall 2016
Note: Deletions are strikethroughs. Insertions are underlined.
Catalog Copy
Data Science and Business Analytics
- M.S. in Data Science and Business Analytics
- Graduate Certificate in Data Science and Business Analytics
Data Science and Business Analytics Program
dsbaanalytics.uncc.edu
Program Director
Dr. Mirsad Hadzikadic
Director of Student Services
Mr. Joshua Hertel TBACarly Mahedy
The program in Data Science and Business Analytics (DSBA) is a joint venture between the Belk College of Business, College of Computing and Informatics, and the Graduate School at UNC Charlotte. The program offers both a Graduate Certificate and a Master of Science degree designed to prepare students for the complex and rapidly changing data science and business analytics environment.
Master of Science in Data Science and Business Analytics
The Professional Science Master’s (PSM) program in Data Science and Business Analytics (DSBA) is an interdisciplinary program at the intersection of business, computer and information sciences, statistics, and operations research. The program leads to a M.S. in Data Science and Business Analytics. It is a unique blend of business acumen, data understanding, exposure to a diverse set of advanced analytics methods, and hands-on experience designed to help students apply learned knowledge on representative business problems. DSBA graduates are well equipped for employment in a wide variety of data intensive industries, such as financial services, energy, retail/supply chain, or healthcare, where the need for business analysts with quantitative, computational, and sophisticated analytical skills is growing at an explosive pace.
Admission Requirements
Applicants must meet the general Graduate School requirements for admission to Master’s Degree programs. Applications must include all of the materials listed by the Graduate School as typical for Master’s Degree application submissions. In addition to the general requirements for admission to the Graduate School, the following are the minimum admissions requirements for study toward the M.S. in Data Science and Business Analytics:
- Earned undergraduate degree in any scientific, engineering or business discipline or a closely related field
- Undergraduate GPA of 3.0 or above
- Acceptable scores on the verbal, quantitative, and analytical sections of the GRE
- Positive letters of recommendation
- Statement of Purpose outlining the goals for pursuing a graduate education
- Minimum TOEFL score of 220 (computer-based), 557 (paper-based), or 83 (Internet based), or a minimum IELTS band score of 6.5 is required from any applicant whose native language is not English
In addition, the program requires a current working knowledge of at least one higher-level (procedural) language; and a familiarity with computer applications. A minimal background in mathematics is also required, including two semesters of calculus and one semester of statistics. Individuals who have worked at a high professional level in the computer industry or business may be able to substitute work experience for specific subject area admission requirements. Individuals without a business degree or business experience are required to complete an online business fundamentals course prior to enrolling in the program.
Degree Requirements
Thirty-three graduate credit hours are required for the DSBA PSM. Of the 33 graduate credit hours, 24 credit hours are required core courses inclusive of 3 hours for the internship, and 9 credit hours of electives. A minimum of 24 credit hours contributing to the M.S. in Data Science and Business Analytics must be from courses numbered 6000 or higher. A maximum of 6 hours of graduate credit may be transferred. Students may apply all of the credits earned in the Graduate Certificate in Data Science and Business Analytics toward the M.S. in Data Science and Business Analytics with the approval of the DSBA Program Director. All students take the following courses:
Core Requirements (24 hours)
DSBA 6100 Big Data Analytics for Competitive Advantage (3)
DSBA 6400 Internship (3)
DSBAITCS 5122 Visual Analytics (3)
DSBA 6156 Machine Learning (3)
DSBAITCS 6160 Database Systems (3)
DSBAMBAD 6201 Business Intelligence and Analytics (3)
DSBAMBAD 6211 Advanced Business Analytics (3)
DSBAMBAD 6276 Consumer Analytics (3)
Elective Courses (9 hours)
In addition, students choose 3 elective courses from a growing list of Data Science and Business Analytics courses or propose a three-course specialization for approval by the DSBA Program Director. In choosing their 3 electives courses, students must select at least one course from each of the following areas:
Data Science Electives
DSBAITCS 5121 Information Visualization (3)
DSBAITCS 6155 Knowledge-Based Systems (3)
DSBAITCS 6190 Cloud Computing for Data Analysis (3)
DSBAITIS 5510 Web Mining (3)
DSBA 6162 Knowledge Discovery in Databases (3)
DSBA 6265 Advanced Topics in Knowledge Discovery in Databases (3)
DSBAITIS 6500 Complex Adaptive Systems (3)
DSBAITIS 6520 Network Science (3)
Business Analytics Electives
DSBAECON 6112 Graduate Econometrics (3)
DSBAMBAD 6122 Decision Modeling and Analysis via Spreadsheets (3)
DSBAMBAD 6207 Project Management (3)
DSBAMBAD 6208 Supply Chain Management (3)
DSBAMBAD 6277 Social Media Marketing and Analytics (3)
DSBAMBAD 6278 Innovation Analytics (3)
Student-Structured Electives Option
Students may propose a three-course specialization (9 credit hours) in a significant area of interest for approval by the Director of the PSM DSBA Program. In addition to the courses listed in the Data Science and Business Analytics specializations listed above, this specialization may include graduate courses from MS in CS, MS in IT, MBA, MS in Applied Statistics, MS in Mathematical Finance, MS in Economics, and other programs or Departments within the University with approval of the related Department.
Graduate Certificate in Data Science and Business Analytics
The Graduate Certificate in Data Science and Business Analytics provides post-baccalaureate students with the opportunity to reach a demonstrated level of competence in the area of data science and business analytics. The certificate requires fifteen (15) graduate credit-hours of coursework. The certificate may be pursued concurrently with a related graduate degree program at UNC Charlotte.
Admission Requirements
The Graduate Certificate in DSBA is open to all students who hold a B.S. or M.S. degree in any scientific, engineering or business discipline and either are enrolled and in good standing in a graduate degree program at UNC Charlotte or complete their undergraduate degree with a minimum 3.0 GPA.
In addition, the program requires a current working knowledge of at least one higher-level (procedural) language; and a familiarity with computer applications. A minimal background in mathematics is also required, including two semesters of calculus and one semester of statistics. Individuals who have worked at a high professional level in the computer industry or business may be able to substitute work experience for specific subject area admission requirements. Individuals without a business degree or business experience are required to complete an online business fundamentals course prior to enrolling in the program. Transfer credit from another institution is not accepted into this certificate program.
Students pursuing the M.S. in Computer Science, M.S. in Information Technology, and MBA degrees have priority on space in the corresponding ITCS, ITIS, and MBAD classes should demand for the proposed certificate exceed expectations.
Program Requirements
The certificate is awarded upon completion of five graduate level courses (15 credits) in the area of data science and business analytics. A cumulative GPA of 3.0 is required and, at most, one course with a grade of C may be allowed towards the certificate. Students must take five courses, as outlined below, to receive the Graduate Certificate in Data Science and Business Analytics.
Core Requirements
DSBA 6100 Big Data Analytics for Competitive Advantage (3)
DSBAITCS 6160 Data Base Systems (3)
DSBAMBAD 6201 Business Intelligence and Analytics (3)
One of the following courses:
DSBAITCS 5122 Visual Analytics (3)
DSBA ITIS 6520 Network Science (3)
One of the following courses:
DSBAMBAD 6122 Decision Modeling and Analysis (3)
DSBAMBAD 6211 Advanced Business Analytics (3)
DSBAMBAD 6276 Consumer Analytics (3)
Courses In Data Science and Business Analytics (DSBA)
DSBA 5121. Information Visualization. (3) Cross-listed as ITCS and HCIP 5121. Prerequisite: Full graduate standing and enrollment in the DSBA PSM or Graduate Certificate. Information visualization concepts, theories, design principles, popular techniques, evaluation methods, and information visualization applications. (Spring)
DSBA 5122. Visual Analytics. (3) Cross-listed as ITCS and HCIP 5122. Prerequisite: Full graduate standing and enrollment in the DSBA PSM or Graduate Certificate, and approval of the program. Introduces the new field of visual analytics, which integrates interactive analytical methods and visualization. Topics include: critical thinking, visual reasoning, perception/cognition, statistical and other analysis techniques, principles of interaction, and applications. (Fall, Spring)
DSBA 5510. Web Mining. (3) Cross-listed as ITIS 5510. Pre- or corequisites: ITIS 5160, full graduate standing and enrollment in the DSBA PSM or Graduate Certificate. Topics include: measuring and modeling the Web; crawling, Web search and information retrieval; unsupervised learning, supervised learning, semi-supervised learning in Web context; social network analysis and hyperlink analysis; text parsing and knowledge representation. (Spring)
DSBA 6100. Big Data Analytics for Competitive Advantage. (3) Cross-listed as HCIP 6103 and ITCS 6100. Prerequisite: Full graduate standing and enrollment in the DSBA PSM or Graduate Certificate. An introduction to the use of big data as a strategic resource. A focus is placed on integrating the knowledge of analytics tools with an understanding of how companies leverage data analytics to gain strategic advantage. A case approach is used to emphasize hands-on learning and a real-world view of big data analytics. (Fall, Spring)(Fall, On demand)
DSBA 6112. Graduate Econometrics. (3) Cross-listed as ECON 6112. Prerequisite: Full graduate standing and enrollment in the DSBA PSM or Graduate Certificate. Advanced study of the theory and application of statistics to economic problems. Topics include: derivation of least-squares estimators; maximum likelihood estimation; and problems of multicollinearity, heteroskedasticity, and autocorrelation. (Fall, Spring)
DSBA 6122. Decision Modeling and Analysis via Spreadsheets. (3) Cross-listed as MBAD 6122. Prerequisite: MBAD 5141 or equivalent, full graduate standing and enrollment in the DSBA PSM or Graduate Certificate. An analytical approach to the management process. Generalized models for decision making with major emphasis on application of the scientific method to management problems. (Fall, Spring))
DSBA 6155. Knowledge-Based Systems. (3) Cross-listed as ITCS 6155. Prerequisite: ITCS 6162, full graduate standing and enrollment in the DSBA PSM or Graduate Certificate. Knowledge systems; knowledge discovery; association rules; action rules, hierarchical classifiers, cascade classifiers, query languages and their semantics; cooperative and collaborative systems; ontology and metadata; flexible query answering; chase algorithms and data sanitization methods; decision support systems in medicine; and automatic indexing of music. (Spring)
DSBA 6156. Machine Learning. (3) Cross-listed as ITCS 6156 and HCIP 6156. Prerequisite: ITCS 6150, full graduate standing and enrollment in the DSBA PSM or Graduate Certificate. Machine learning methods and techniques including: acquisition of declarative knowledge; organization of knowledge into new, more effective representations; development of new skills through instruction and practice; and discovery of new facts and theories through observation and experimentation. (Fall, Spring)
DSBA 6160. Database Systems. (3) Cross-listed as ITCS 6160 and HCIP 6160. Prerequisite: Full graduate standing and enrollment in the DSBA PSM or Graduate Certificate. The modeling, programming, and implementation of database systems. Focuses on relational database systems, but may also address non-relational databases or other advanced topics. Topics include: (1) modeling: conceptual data modeling, ER diagram, relational data model, schema design and refinement; (2) programming: relational algebra and calculus, SQL, constraints, triggers, views; (3) implementation: data storage, indexing, query execution, query optimization, and transaction management; and (4) advanced: semi-structured data model, XML, and other emerging topics. (Fall, Spring)
DSBA 6162. Knowledge Discovery in Databases. (3) Cross-listed as ITCS 6162 and HCIP 6162. Prerequisite: DSBA 6160 and full graduate standing and enrollment in the DSBA PSM. The entire knowledge discovery process is covered in this course. Topics include: setting up a problem, data preprocessing and warehousing, data mining in search for knowledge, knowledge evaluation, visualization and application in decision making. A broad range of systems, such as OLAP, LERS, DatalogicR+, C4.5, AQ15, Forty-Niner, CN2, QRAS, and discretization algorithms will be covered. (On Demand)
DSBA 6265. Advanced Topics in Knowledge Discovery in Databases. (3) Cross-listed as ITCS 6265. Prerequisite: DSBA 6162 or permission of the instructor, and full graduate standing and enrollment in the DSBA PSM. Information visualization in data mining and knowledge discovery, predictive data mining, mining of multimedia sources, mining of unstructured data, distributed data mining, mining of Web data/information, mining complex types of data, mining of biotechnology data, applications, and trends in data mining. (On Demand)
DSBA 6190. Cloud Computing for Data Analysis. (3) Cross-listed as ITCS 6190 and ITCS 8190. Prerequisites: ITCS 6114 or permission of department, familiarity with Java, Unix, Data Structures and Algorithms, Linear Algebra, and Probability and Statistics; good programming skills and a solid mathematical background. Introduction to the basic principles of cloud computing for data-intensive applications. Focuses on parallel computing using Google’s MapReduce paradigm on Linux clusters, and algorithms for large-scale data analysis applications in web search, information retrieval, computational advertising, and business and scientific data analysis. Students read and present research papers on these topics, and implement programming projects using Hadoop, an open source implementation of Google’s MapReduce technology, and related NoSQL technologies for analyzing unstructured data. (Fall)
DSBA 6201. Business Intelligence and Analytics. (3) Cross-listed as MBAD 6201. Prerequisite: MBAD 5121, full graduate standing and enrollment in the DSBA PSM or Graduate Certificate. An overview of the business approach to identifying, modeling, retrieving, sharing, and evaluating an enterprise’s data and knowledge assets. Focuses on the understanding of data and knowledge management, data warehousing, data mining (including rule-based systems, decision trees, neural networks, etc.), and other business intelligence concepts. Covers the organizational, technological and management perspectives. (Fall, Spring)
DSBA 6207. Business Project Management. (3) Cross-listed as MBAD 6207. Prerequisites: MBAD 5121 or equivalent and MBAD 6141, Full graduate standing and enrollment in the DSBA PSM or Graduate Certificate. Project management is widely used in a variety of business environments to manage complex, non-routine endeavors. Examples of projects include consulting and process improvement projects, advertising projects, and technology projects. This course focuses on tools, techniques, and skills for business project management, with attention to both the quantitative and the qualitative aspects of project management. Topics include: project evaluation, estimation, monitoring, risk management, audit, managing global projects, outsourcing, and project portfolio management. Students also gain experience using Project Management Software. (Spring)
DSBA 6208. Supply Chain Management. (3) Cross-listed as MBAD 6208. Prerequisites: MBAD 6141,full graduate standing and enrollment in the DSBA PSM or Graduate Certificate. Supply chain management is concerned with all of the activities performed from the initial raw materials to the ultimate consumption of the finished product. From a broad perspective, the course is designed to examine the major aspects of the supply chain: the product flows; the information flows; and the relationships among supply chain participants. The course content is interdisciplinary in nature and will cover a variety of topics such as supply chain information technologies, supply chain design, strategic alliances between supply chain participants and supply chain initiatives. (Spring, On demand)ystems, decision trees, neural networks, etc.), and other business intelligence concepts. Covers the organizational, technological and management perspectives. (Fall, On demand)
DSBA 6211. Advanced Business Analytics. (3) Cross-listed as MBAD 6211. Pre-requisite: MBAD 6201 or ITCS 6162, full graduate standing and enrollment in the DSBA PSM or Graduate Certificate. An in-depth study of applications of data analytics techniques to discover non-trivial relationships that are understandable, useful, and actionable to decision makers. A case approach is used to emphasize hands-on learning and real-world deployment of business analytics. (Fall, Spring)
DSBA 6276. Consumer Analytics. (3) Cross-listed as MBAD 6276. Prerequisite: MBAD 6270, full graduate standing and enrollment in the DSBA PSM or Graduate Certificate. The utilization of analytics techniques in marketing decision-making and consumer strategy. Involves the extraction of hidden insight about consumers from structured and unstructured Big Data, and the translation of that insight into a market advantage. Applications in areas such as consumer targeting, product innovation, and promotion strategy. (Fall)
DSBA 6277. Social Media Marketing and Analytics. (3) Cross-listed as MBAD 6277. Prerequisite: MBAD 6270, full graduate standing and enrollment in the DSBA PSM or Graduate Certificate. The utilization of social media in marketing strategy and tactics. Topics include: the use of social media in building brand strength and equity, as a customer acquisition tool, and as a customer relationship management tool. The utilization of analytics in effective social media marketing. (Spring)
DSBA 6278. Innovation Analytics. (3) Cross-listed as MBAD 6278. Prerequisite: MBAD 6270 or permission of department, full graduate standing and enrollment in the DSBA PSM or Graduate Certificate. The comprehension and application of text analytics as a tool to examine unstructured qualitative information to generate innovations. Identifying the various sources of consumer insight and using them in innovation strategy. Understand how to differentiate between what consumers want versus what they say. (Spring)
DSBA 6400. Internship. (3) Prerequisite: Completion of 21 credit hours of core course requirements. A data science or business analytics project is chosen and completed under the guidance of an industry partner. Each student’s internship project program must be approved by the program director. A proposal form must be completed and approved prior to registration and the commencement of the internship. A mid-term report and a final report to be evaluated by the industry partner and supervising faculty. Grading is by the supervising faculty in consultation with off-campus supervisor at the internship organization. Graded on a Pass/No Credit basis. (Fall, Spring, Summer)
DSBA 6500. Complex Adaptive Systems. (3) Cross-listed as HCIP 6500, ITCS 6500, ITCS 8500, ITIS 6500 and ITIS 8500. Prerequisite: Full graduate standing and enrollment in the DSBA PSM or Graduate Certificate. Complex adaptive systems (CAS) are networked (agents/part interact with their neighbors and, occasionally, distant agents), nonlinear (the whole is greater than the sum of its parts), adaptive (the system learns to change with its environment), open (new resources are being introduced into the environment), dynamic (the change is a norm), emergent (new, unplanned features of the system get introduced through the interaction of its parts/agents), and self-organizing (the parts organize themselves into a hierarchy of subsystems of various complexity). Ant colonies, networks of neurons, the immune system, the Internet, social institutions, organization of cities, and the global economy are a few examples where the behavior of the whole is much more complex than the behavior of the parts. This course will cover those and similar topics in an interactive manner. Examples of our current research effort will be provided. Topics include: Self-organization; emergent properties; learning; agents; localization affect; adaptive systems; nonlinear behavior; chaos; complexity. (Spring)
DSBA 6520. Network Science. (3) Cross-listed as HCIP 6520 ITIS 6520, and ITIS 8520. Prerequisite: Full graduate standing and enrollment in the DSBA PSM or Graduate Certificate.Network Science helps students design faster, more resilient communication networks; revise infrastructure systems such as electrical power grids, telecommunications networks, and airline routes; model market dynamics; understand synchronization in biological systems; and analyze social interactions among people. It examines the various kinds of networks (regular, random, small-world, influence, scale-free, and social) and applies network processes and behaviors to emergence, epidemics, synchrony, and risk. This course integrates concepts across computer science, biology, physics, social network analysis, economics, and marketing. (Fall)
Computer Science Courses (ITCS)
See descriptions of ITCS courses under “Computer Science” in the College of Computing and Informatics section of this Catalog.
Information Technology Courses (ITIS)
See descriptions of ITIS courses under “Information Technology” in the College of Computing and Informatics section of this Catalog.
Business Administration Courses (MBAD)
See descriptions of MBAD courses under “Business Administration” in the College of Business section of this Catalog.