The threats to business are real, evolving, and always present. A solid plan of defense that secures companies, data, intellectual property, and systems isn't a suggestion; its an absolute necessity. Students will focus on the security implications of seven main topic areas, including IT operations, hacking, incident response, and defensive technologies.
Provides an overview of a business from both a strategic process perspective and as a system and introduces a broad conceptual framework. The remaining ICE sessions provide more specific concepts and techniques. A current business, as well as cases and lecture, is used to develop the framework. Topics include the transformation of business, the role of the general manager, systems thinking and process management, strategic thinking and information systems, global strategy and culture, organizational architecture, information architecture, and the value chain. Prerequisite: Third-year Commerce standing.
This course provides an overview of key quantitative and qualitative tools necessary for making effective individual- and team-based decisions. It includes a variety of topics that each emphasize three themes central to managerial decision making: (1) Data Management and Data Visualization, (2) Quantitative Analysis, and (3) Perception and Judgment. .
This course will provide knowledge of product management in combination with project management skills, both of which are necessary for the management of the digital product innovation process end-to-end. Course consists of seminars on roles of the product & project manager, managing innovation, selecting projects, stakeholder mgmt, team mgmt, schedule & time mgmt, risk mgmt, & on leading changes. Workshops on digital innovation, agile & waterfall methods.
Provides an introduction to the management of database systems and how business intelligence can be used for competitive advantage. The course uses an applied, problem-based approach to teach students the fundamentals of relational systems including data models, database architectures, database manipulations (e.g., SQL), and BI tools. Prerequisite: Undergraduate Commerce or Instructor Permission
This course provides the opportunity to offer new topics in the subject of Commerce.
Covers end-to-end processes relating to the capture, organization, use, and protection of data for analytical purposes. You will learn how to build an optimized relational database and use SQL to extract data to support an organization's analytics strategy and provide important managerial insights from raw data. Extraction, transformation, load (ETL) and data privacy/security will also be discussed in the context of modern organizations.
In the second capstone course you will assess the business impact of your solution and should be done in conjunction with the sponsoring company. Key assessment questions may include: a) how much money (or other resources) will the proposed solution save? b) How many new customers will the proposed solution attract? c) how much money will current customers spend? The core deliverable is a report on the business impact your proposed solution.
Multivariate statistics training to analyze Big Data sets. The course covers discrete choice modeling (logistic and probit models), classification techniques (discriminant and cluster analyses), data reduction techniques (factor analysis), and advanced predictive techniques (regression models with interactions and curvilinear effects, structural equation modeling, and factorial ANOVA). Trains students on IBM-SPSS, SAS, and R.
The primary objective of Project Management is to provide a blend of theoretical knowledge and practical skills necessary for the effective management of projects. To this end, the course is closely tied to the Project Management Body of Knowledge (PMBOK, as espoused by the Project Management Institute) and consists of seminars on such topics as planning, stakeholder management, human resource management, global/virtual teams, risk management. Prerequisites: Restricted to MS in Commerce students.
This course is focused on harnessing the power of unstructured data to perform advanced analytical techniques. Students will be exposed to big data technologies (NoSQL, Hadoop, etc.) to understand how to manage and interact with large, complex data sets. We will also cover various analytical and machine learning techniques that can apply to these data, with particular attention to text data from reports, articles, and social media.
This course provides an introduction to management and use of data in business. The course emphasizes understanding fundamentals of relational database systems design and querying using SQL and provides a basic understanding of developments and trends in Business Intelligence/Analytics, with implications for accountants. Restricted to MS in Accounting Students.
McIntire aims to train students on the latest business practices and decision-making tools. While this statement describes the entire MS-Commerce curriculum, this 1.5 credit hour current topics course is designed to track analytical tools likely to change more frequently than our other courses. The specific topics and tools covered are subject to change annually, as marketplace demands change.