Management Information Systems

Master of Science

This course will integrate many business foundations in support of MIS students in the MS program. In today's environment, IT solutions have to support the competitive needs of organizations and recognize the inter-organizational nature of business processes. In addition, the IT solutions have to support the financial well-being of a firm as well as its responsibility to various stakeholders. This course uses five modules: business strategy in a global environment, process analysis and re-design in an ever-expanding value chain; IT in support of these business processes, economic justification and social implications.

This course exposes you to a broad range of computer systems and information security topics. It is designed to provide a general knowledge of measures to insure the confidentiality, availability, and integrity of information systems. Topics range from hardware, software, and network security to INFOSEC, OPSEC, and NSTISS overviews. Components include national policy, threats, countermeasures, and risk management among others.

This course introduces the student to fundamentals of database analysis, design and implementation. Emphasis is on practical aspects of business process analysis and the accompanying database design and development. Topics covered include: conceptual design of databases using the entity relationship model, relational design and normalization, SQL and PL/SQL, web based database design and implementation using Oracle or some other modern Database Management Systems. Students may be required to work with an organization in understanding their business requirements, developing a detailed set of requirements to support business processes, and designing and implementing a web based database application to support their day- to-day business operations and decision making. Students will acquire hands-on-experience with a state-of-the-art database management system such as Oracle or Microsoft SQLServer, and web-based development tools. 

Service-oriented architectures and computing have emerged as the core of the next generation of information systems. This course focuses on analysis and design of information systems with a service-oriented perspective. This course also covers process analysis and modeling to certain degree since it is the foundation of service-oriented architectures. This course will include some of the following topics: introduction to service-oriented architecture, overview of system sourcing strategies, specification of service level agreements, software development approaches, process-driven system integration, introduction to Unified Modeling Language. The course may involve a group project that analyzes and design a real-world system in a corporate setting. 

This course provides an in-depth knowledge of data communications and networking requirements, including networking technologies, hardware and software. This course has two objectives. First, it focuses on basic networking standards and protocols. Second, students will learn to evaluate, select and implement different data network options and prepare a cost-benefit analysis for a proposed solution.

Corporations today are said to be data-rich but information poor. For example, retailers can easily process and capture millions of transactions every day. In addition, the widespread proliferation of economic activity on the Internet leaves behind a rich trail of micro-level data on consumers, their purchases, retailers and their offerings, auction bidding, music sharing, so on and so forth. Data mining techniques can help companies discover knowledge and acquire business intelligence from these massive datasets. This course will cover data mining for business intelligence. Data mining refers to extracting or “mining” knowledge from large amounts of data. It consists of several techniques that aim at discovering rich and interesting patterns that can bring value or “business intelligence” to organizations. Examples of such patterns include fraud detection, consumer behavior and credit approval. The course will cover the most important data mining techniques --- classification, clustering, association rule mining, visualization and prediction. 

Students will integrate their knowledge from their program of study and apply it to a problem area in MIS. Each student will write a significant report based on the results of his or her work.