Management Information Systems

Explores a problem solving methodology that employs programming. Emphasis upon identifying capabilities and limitations of the programming approach. Learn skills and techniques to define business problems, design solution processes, develop program specifications, code, debug, and document and defend solutions.

Theoretic and practical issues related to the management of a data base in a business environment including: the role of databases and database applications in contemporary organizations; data modeling using entity-relationship models; fundamentals of the relational data model and its implementation with SQL; characteristics of distributed databases and Client/Server data base technologies.

Concepts, tools and techniques in the analysis and design of computer-based information systems; major issues and decision making in each phase of the development life cycle, application of creativity and innovation to the practice of systems analysis and design, skills necessary for modeling the data and processing requirements of an information system using an automated development tool, a systems development team project approach.

Management and development enterprise computing concepts and applications in today's organization; integration of information systems in real time for support of internal functions; integration of different E-Commerce front ends with the Enterprise Resource Planning (ERP) system for extension of their functionality.

Introduces theory, techniques, and tools needed to build sucessful E-business applications. It includes a survey of business web applications and their underlining technologies. Students learn to use client-side and server-side techniques, such as JavaScript, CGI, and Active Server Page, to building web applications. As a part of the course, students will be required to construct a functional database-driven web application by utilizing the technologies covered in class.

Fundamental issues associated with Customer Relationship Management (CRM) and Data Analytics, theoretical and practical, such as designing and building a data warehouse, building and populating info-cubes, report generation with SAP BW, data mining, business intelligence technologies, and extension of CRM to the Internet.

This course examines concepts, processes, and tools related to business intelligence (BI) through the lens of Generative AI. Students will learn systematic approaches for architecting an end-to-end BI pipeline using the industry's leading """Modern Data Stack""""."

This course focuses on the emerging and disruptive business technologies - like augmented reality, intelligent systems, Internet-of-Things and location-based services - likely to impact current and future business models and processes the most.

Covers use of machine learning algorithms in business decision making and ethical challenges. Involves data preparation, preprocessing, coding and implementation of ML models including regression, forests, k nearest neighbors, dimensionality reduction, along with deeper learning models such as neural networks.

The course enables students to understand and develop AI-enabled applications that leverage machine learning, generative AI, and AI agent platforms and tools to improve and automate business models and processes for competitive advantage.

Employment with approved business firms where various meaningful assignments are performed with appropriate training, instruction, and supervision.

Study with faculty member's guidance in area of special interest to student.

Full-time employment with an approved firm in the area of MIS where experience is gained through appropriate training, instruction, and supervision. Course does not fulfill the requirements of the major. Prerequisite: MIS major with junior status; minimum gpa requirements will vary; approval of DIT Department Chair and Director of Center for Student Advising and Professional Development required.