MS-BA cloud computing and tech consulting track

Ensuring the foundational understanding of contextualized analytics within the business enterprise continuum by covering how data flows and is managed across the landscape of enterprise business processes.

Provides a foundation in programming fundamentals, the skills to combine and manipulate structured and unstructured data, and the ability to summarize, visualize, and draw insights from the data. This course may be waived with demonstrated Python proficiency.

Provides a solid foundation and deeper understanding of the use of quantitative modeling tools and techniques to solve problems faced in modern supply chains. Uses Excel workbooks to implement the appropriate quantitative methods, including forecasting demand, capacity planning of a manufacturing line and the line cycle time as it pertains to parts inventory management.

Charting a roadmap for data-driven decision making and getting a practical understanding of how IT tools and techniques can allow managers to extract predictive analytics and patterns from primarily numeric data.

Addresses the use of analytics tools and techniques to enhance the ability of quality management approaches to improve processes. Introduces modern quality management approaches including six sigma and design for six sigma. Covers the define, measure, analyze, improve and control (DMAIC) improvement cycle: the core process used to drive six sigma projects. DMAIC refers to a data-driven improvement cycle used for improving, optimizing and stabilizing business processes and designs. Provides an analytics roadmap to help users work through the DMAIC problem-solving process.

This course explores fundamental cloud computing infrastructure and services, and critical strategic considerations for all organizations, regardless of where they are in their cloud journey. The architectures and services covered are foundational to modern enterprise systems, data, and analytics.

Explains the skills and knowledge necessary for mastery of the use of quantitative modeling tools and techniques to support a variety of business decisions. Also explores deterministic optimization techniques, including linear programming, nonlinear programming, integer programming; network models and a brief introduction to metaheuristics. Covers the use of these models for a variety of common business problems. Practical application of these models uses Excel and standalone software. Also studies how to ensure that these solutions work in a wide variety of situations (what-if analysis).

Provides an overview of the project management process groups and knowledge areas (defined by the PMBOK) and focuses on the application of key concepts, tools and techniques for delivering on-time, on-budget IT project and services that meet end-user needs.

Provides a broad survey of information security and controls, utilizing the COBIT framework to illustrate how information security and controls contribute to effective IT governance. Develops an understanding of the issues associated with information security and effective IT governance, with particular emphasis on how management contributes to the effectiveness of an organization's information security program.

Explores modern artificial intelligence (AI) technology, applications, techniques and their implications for business. People, process and technology factors related to the innovation and adoption of AI in the commercial enterprise and how it shapes the competition and society in the future. Also covers implications for information systems professionals as it pertains to managing the AI infrastructure (robots, algorithms, platforms).

Explores decision models and frameworks applied to assess, evaluate and implement emerging technologies. Explains the principles of sustaining and disruptive technological innovation on the adoption and diffusion of emerging technologies. Discusses the technical, industrial and legal parameters that enable convergence and commoditization of technologies.

Explores how to support informed decision making and extract predictive analytics and patterns from nonnumeric data by leveraging tools and techniques to analyze unstructured data.

Instills balanced and disciplined view of IT and business with their interplay. Assigns cases and assignments involving the symbiotic relationship of IT and business to provide real-world exposure for critical thinking and engaging discussion.

Focuses on a system designed to help students take an active role in their career development through self-reflection, skills and values assessment, market research and identifying potential roadblocks to obtaining an internship or full-time role after graduation. Also introduces the concept of a personal narrative and provides experiential learning opportunities to refine their own personal narrative and understand how to fine-tune and tailor it for a variety of career applications.

The design of insightful business data visualizations and dashboards to improve business decision making. Applies advanced data visualization techniques to make sense of large data sets including temporal, geospatial, topical and business data while also making it easier to digest, present and utilize for business needs and users.

Preparation of a supervised applied project that is a graduation requirement in some professional majors.