Information Systems and E-Business Concentration

This course is designed to provide students with a basic understanding of business data communications. The objective of the course is to provide students with a firm foundation for covering more advanced topics in subsequent courses. The student will develop an understanding of networks including the internet and the development of World Wide Web based applications. The course will also cover the basic principles of network operating systems concepts and the role of network operating systems in developing Web applications. The course includes extensive coverage of business telecommunication including voice and data. Coverage is extended to coding and digitizing, modems, protocols, and network architectures as well as management aspects. Cases on telecommunications and electronic commerce, as well as current readings, will also be part of the pedagogy.

Credits: 3.00
Semesters offered: Fall 2019

Fall 2019 (08/26/2019 - 12/06/2019)

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: 3.00
Semesters offered: Fall 2019 | Summer 2019

Fall 2019 (08/26/2019 - 12/06/2019)

Summer 2019 (06/24/2019 - 08/16/2019)

This course provides an introduction to the systems development life cycle (SDLC) emphasizing the recent adaptive approaches to SDLC, such as the unified process life cycle and agile methods. The course focuses on the disciplines of business modeling, requirements analysis, and logical design and utilizes the Unified Modeling Language (UML) for analysis, modeling, and design of business-oriented information systems. Information assurance issues of system controls and security are covered with respect to their impact on system requirements and design models.

Credits: 3.00
Semesters offered: Spring 2020

Spring 2020 (01/27/2020 - 05/09/2020)

This course teaches the technical and managerial skills needed in developing predictive analytics applications which are used by customer-centric corporations - retail, financial, communication, and marketing groups - to help make decisions involving complex systems. The course concentrates on a set of well-known predictive analytics methods to support business decision making. Topics such as association rule mining, decision trees, neural networks, regression analysis and cluster analysis are covered in great depth. Extensive hands-on experience using software such as SAS Enterprise Miner is provided.

Credits: 3.00
Semesters offered: Fall 2019 | Spring 2020

Fall 2019 (08/26/2019 - 12/06/2019)

Spring 2020 (01/27/2020 - 05/09/2020)

Large scale computing environments aggregate resources from many autonomous computers to satisfy the information processing needs of modern enterprises. This course introduces techniques for creating functional, usable, high-performance distributed systems. Objectives are twofold: (1) gain a solid understanding of the technical issues, concepts and systems in the rapidly advancing technologies in distributed computing, and (2) acquire substantial knowledge on how to work with big data in distributed environments. The course is organized into two parts: study of DCS technologies, and study of large scale systems. We will discuss communication and networking services, application support services, large scale distributed system design, data management and interoperability of systems including consistency and data replication. Students will learn to use a framework for data intensive distributed applications (Apache Hadoop) and an associated parallel programming model, MapReduce.

Credits: 3.00
Semesters offered: