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Semester One
This course is designed to provide students with a basic understanding of database management systems (DBMS) and the skills needed to design and implement a relational database. Students will be introduced to data modeling concepts, modeling tools, the process of transforming conceptual models into relational database designs, and finally the steps needed to implement those designs. Emphasis is placed on Entity-Relationship diagramming, data normalization, database administration, and data definition, data manipulation and query development using Structured Query Language (SQL). Other topics covered include: object-oriented databases, database security and integrity, web/database integration, application development in a Client/Server environment, distributed databases, data warehousing, data mining and knowledge management via the Internet to support electronic commerce. Readings, lectures, interactive case assignments and a database design project reinforce the role of DBMS in supporting organizational systems, transaction processing and decision support applications.
Credits: 3
Semesters offered: Fall 2023
This course covers the fundamental concepts in statistics that are essential for business and data analytics. Probability Theory and Sampling Theory are the two foundations of both descriptive and predictive forms of analytics. Building from these foundations, students are introduced to the statistical concepts of data analysis. Topics covered include: descriptive statistics, probability theory, discrete and continuous probability distributions, sampling theory, estimation, hypothesis testing, distribution fitting using chi-square tests, simple and multiple linear regression, introduction to causal modeling and predictive data analytics. MS-Excel based data modeling will be used extensively throughout the exposition of the concepts.
Credits: 3
Semesters offered: Fall 2023 | Spring 2024
Total credits: 6
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The focus of this course will be on technology management and developing an Internet-based business or extension to an existing business. The course will integrate concepts from economics, organizational strategy, entrepreneur-ship, and Web design. Topics to be covered in the course include: aligning technology and strategy; models of diffusion and innovation; characteristics of information and digital goods; identifying potential Web-applications and information products for solving a problem and/or identifying a business opportunity; intellectual property rights; pricing issues related to information goods; developing a business plan for a venture capital proposal; launching the e-business; designing Web based applications for usability; and strategies for successfully implementing systems. Case studies, lectures, guest speakers, and an integrated E-business project will be used to understand the complexities of the current business environment.
Credits: 3
Semesters offered: Fall 2023 | Spring 2024
This course is designed to provide students with a basic understanding of database management systems (DBMS) and the skills needed to design and implement a relational database. Students will be introduced to data modeling concepts, modeling tools, the process of transforming conceptual models into relational database designs, and finally the steps needed to implement those designs. Emphasis is placed on Entity-Relationship diagramming, data normalization, database administration, and data definition, data manipulation and query development using Structured Query Language (SQL). Other topics covered include: object-oriented databases, database security and integrity, web/database integration, application development in a Client/Server environment, distributed databases, data warehousing, data mining and knowledge management via the Internet to support electronic commerce. Readings, lectures, interactive case assignments and a database design project reinforce the role of DBMS in supporting organizational systems, transaction processing and decision support applications.
Credits: 3
Semesters offered: Fall 2023
This course covers the fundamental concepts in statistics that are essential for business and data analytics. Probability Theory and Sampling Theory are the two foundations of both descriptive and predictive forms of analytics. Building from these foundations, students are introduced to the statistical concepts of data analysis. Topics covered include: descriptive statistics, probability theory, discrete and continuous probability distributions, sampling theory, estimation, hypothesis testing, distribution fitting using chi-square tests, simple and multiple linear regression, introduction to causal modeling and predictive data analytics. MS-Excel based data modeling will be used extensively throughout the exposition of the concepts.
Credits: 3
Semesters offered: Fall 2023 | Spring 2024
*MGQ 606 is only required for students without a business background.
• Three electives (3 credits each)
*Students without a business background are required to take MGG 503 and MGQ 606; students with a business background may be waived from these courses.
MGS 613 is a component of the Information Assurance certificate. If you take three of these elective courses, you will be eligible for the certificate in addition to the MS degree. See additional information on the Information Assurance certificate.