Core Classes
Get a solid foundation of technical and quantitative knowledge in data analytics, and develop your data presentation and communication skills from eight core courses (24 credits).
(BUAN 640) – 3 credits
This course provides students with a basic understanding of the role of statistics in the gathering of data, the creation of information and its use in decision-making. Students will learn methods for summarizing data, both numerically and graphically, and for drawing conclusions from sample data. Statistical analyses will be carried out using the computer and statistical software. The focus of the course is on how statistical methods can be applied to business problems to improve outcomes; stress is placed on the design of statistical studies, collection of data, and the interpretation of results. The course will also focus on interpreting computer output and less on generating numbers through hand calculations.
Prerequisite: NONE.
(BUAN 600) - 3 credits
This course teaches students how to perform data analysis using spreadsheet-based methods to effectively and efficiently solve management problems. Students will learn how to effectively build, present and communicate advanced Excel spreadsheet models, forecasting models, optimization models and simulation models to drive managerial decision making. Students will also learn how to build interactive, data driven dashboards using Power BI to discover new insights and monitor key performance indicators.
Prerequisites: NONE
(BUAN 610) - 3 credits
This course will focus on developing the ability to understand the business needs for data insights, crafting those into an analytics problem statement, and developing a coherent and persuasive narrative of any data findings. Students will learn to create well-crafted data narratives and dashboards for business leaders while being able to translate insights into managerial decisions. Students will also be able to prepare raw data sets for their data narratives, executive summaries and technical memos. The Data Narratives course focuses on providing these fundamental data narrative and storytelling abilities while leveraging various tools to assist in the process.
Prerequisites: NONE
(BUAN 620) - 3 credits
This course covers the life cycle of data for analytics from the structure of relational and non-relational data stores, though the extraction, transformation, and loading (ETL) process, and into the analysis and presentation of data using data dashboards. Students will learn and practice acquiring, extracting, cleaning, and loading data from databases and other data stores. Students will learn to interpret and create data models, write and interpret the results of Structured Query Language (SQL), practice and apply industry ETL tools to solve business problems, and effectively communicate about data through the use of a dashboarding tool.
Prerequisites: NONE.
(BUAN 630) - 3 credits
In today's rapidly evolving business landscape, AI has emerged as a transformative force, reshaping industries, and redefining the rules of success. This course aims to bridge the gap between AI technology and business strategy, enabling students to integrate AI into their organizations and drive measurable results effectively. Through a combination of real-world case studies and hands-on projects, students will explore the various applications of AI in business, including customer experience enhancement, operational optimization, predictive analytics, and product innovation. The course will cover key AI technologies such as generative AI, machine learning, natural language processing, and computer vision, focusing on their practical implementation within a business context.
Prerequisite: None
(BUAN 650) - 3 credits
Gain a better understanding of data analysis for business research, emphasizing the interpretation of data rather than calculations. Develop techniques commonly used in business such as logistic regression, two-way analysis of variance and statistics for scale development. These skills are relevant for students involved in marketing research and survey development. Course deliverables will include a project, potentially based on a situation or analysis from your workplace or industry.
Prerequisite: BUAN 640.
(SEIS 603) - 3 credits
Learn the technical concepts of managing vast amounts of unstructured, semi-structured and structured data, collectively called “Big Data.” Learn why big data sets must be distributed and examine the issues that distribution introduces. Start by outlining the basic concepts on which distributed data sets are handled. Once that foundation is defined, move on to study the software tools that we use to work with big data sets for an in-depth analysis of the concepts.
(BUAN 799) - 3 credits
This application-focused course provides the opportunity for students to experience a real-time business analytics project. Under faculty guidance and mentoring, small teams of students will work together to implement the breadth of methods and skills developed throughout the MSBA program to manage all aspects of client and project management; develop the project deliverables including business problem analysis, data transformation and analysis; and presentation of the results at the client site. The course will begin with limited on-campus meetings, then transition to a flexible “directed study” format with regular required check-ins with the faculty leader, providing ample time for the team to complete the project work. Teams will use online collaboration software tools for communication and project coordination.
Prerequisite: 21 credits completed