Information Systems Curriculum Overview

The cross-disciplinary curriculum ensures graduates of the Information Systems master's program know how to assess a company's information systems needs, and are able to manage technology projects to meet the needs of the business and its stakeholders. Students also refine their communication and team skills to ensure they can clearly communicate with both business and technology representatives.

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Business core

This course deals with the basic problems of managing a project, defined as a temporary organization built for the purpose of achieving a specific objective. Both operational and conceptual issues will be considered. Operational issues include definition, planning, implementation, control, and evaluation of the project. Conceptual issues include project management vs. hierarchical management, matrix organization, project authority, motivation, and morale. Cases will be used to illustrate problems in project management and how to resolve them.
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Corporate financial management requires the ability to understand the past performance of the firm in accounting terms; while also being able to project the future economic consequences of the firm in financial terms. This course provides the requisite survey of accounting and finance methods and principles to allow technical executives to make effective decisions that maximize shareholder value.
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Information Systems core

This course focuses on data and database management, with an emphasis on modeling and design, and their application to decision support. The course is organized around the following general themes: Strategic Data Planning, Data Governance, Enterprise Data Integration, Data Management Approaches, Data Design for Transaction Processing vs. Decision Support, Data Management Functions, Abstraction and Modeling, Data- and Information Modeling (ER, Object-oriented), Database Schemas (Conceptual Schema), Database Design (Functional Dependencies and Normalization), Query languages (SQL, DDL, QBE), Metadata Development and Application, Data Quality Approaches, Master and Reference Data Management (e.g., Customer and Product Data), Temporal Data, Data, Analytics, and Business Performance, Introduction to Data Warehousing, OLAP, OLTP, and Data Mining, Strategic Data Policies and Guidelines (e.g. Enterprise Data and Integration, Governance, Markets, Customers, and Competitors, Leadership, Analysts and Knowledge Worker Skills and Training, Communities of Analysts). There are numerous case studies and modeling projects throughout the course.
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IT organizations must be able to leverage new technologies. This course focuses on how organizations can effectively and efficiently assess trends and emerging technologies in data and knowledge management, information networks, and analyzing and developing application systems. Students will learn how to help their organizations define, select, and adopt new information technologies.
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This course focuses on the issues surrounding the design of an overall Information Technology architecture. The traditional approach in organizations is to segment the problem into four areas network, hardware, data, and applications. Instead, this course concentrates on the interdependencies among these architectures. In addition, this course will utilize management research on organizational integration and coordination. The student will learn how to design in the large, make appropriate choices about architecture in relationship to overall organization goals, understand the different mechanisms for coordination available, and create a process for establishing and maintaining an ongoing enterprise architecture.
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The objective of this course is to address the important question, "How does one improve the alignment of business and Information Technology strategies?" The course is designed for advanced graduate students. It provides the student with the most current approaches to deriving business and Information Technology strategies, while ensuring harmony among the organizations. Topics include business strategy, business infrastructure, IT strategy, strategic alignment, methods/metrics for building strategies, and achieving alignment.
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You will also choose one of the following to complete the Information Systems core.

This course explores data-driven methods that are used to analyze and solve complex business problems. Students will acquire analytical skills in building, applying and evaluating various models with hands-on computer applications. Topics include descriptive statistics, time-series analysis, regression models, decision analysis, Monte Carlo simulation and optimization models.
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This course will focus on data mining and knowledge discovery algorithms and their applications in solving real business and operation problems. We concentrate on demonstrating how discovering the hidden knowledge in corporate databases helps managers make near-real-time decisions. The course begins with an introduction to data mining and knowledge discovery in databases. Data preprocessing, K-nearest neighborhood algorithms, machine learning and decision trees, artificial neural networks, clustering, and algorithm evaluation techniques will be covered. Practical examples and case studies will be present throughout.
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Specialization

The master's program includes four electives that allow you to explore an area of interest in greater depth. Students seeking a more structured approach can use some of those elective courses to pursue one of the concentrations listed below.

This concentration gives students the perspective and technical skill required to work in the highly fluid area of cybersecurity. Courses taken as part of this concentration will support your preparation for important industry certification exams.

FIN 545 Financial Cybersecurity
MIS 645 Cybersecurity Principles for Managers
BIA 670 Risk Management

With advisor permission, you may substitute one of the above courses with a different cybersecurity elective.

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Business core