Data is everywhere and analysts are using that data every day to help organizations make critical business decisions. From predicting spending habits to monitoring the growth of a public health crisis, data scientists collect, manage and analyze the data needed to make informed decisions. With guidance from expert College of Business faculty at Bowie State, today’s business administration majors studying data analytics are preparing to become tomorrow’s leaders in this fast-growing field. Problem-based learning, capstone projects and application of latest information technology are the foundation of the program, providing students with a high-impact, experiential education that positions them for success.
The Data Analytics Concentration program goals are:
- Produce graduates with strong knowledge and Skills of data science and analytics’ theories, methods, models, process, technologies and tools.
- Produce graduates who will be able to solve local, national and global problems using big data and analytics.
- Produce graduates with strong problem-solving skills.
- Produce graduates with strong critical thinking and analytical skills.
- Produce graduates who will create new business and innovative solutions using advanced and emerging data analytics techniques and technologies.
- Produce graduates who can effectively tell-stories from the results of analytics using oral, written and visual forms of communication.
The expected learning outcomes for the Data Analytics Concentration expected learning are:
- Able to give examples and explain the role of big data for discovery of solutions for real-world problems.
- Able to explain the data science and analytics theories, methods, models and process.
- Able to explain big data and its applications.
- Able to apply data management principles relating to data representation, storage, retrieval and analysis: Able to prepare data-big or small-for analysis for a given problem.
- Able to develop model-based solutions for a given problem with datasets using statistical techniques and machine learning techniques.
- Able to evaluate model-based solutions for a given problem with datasets using statistical techniques and machine learning techniques.
- Able to present and communicate outcomes of analytics visually.
- Able to demonstrate critical thinking skills associated with problem identification, problem solving and decision-making using data and analytics.
Curriculum Design, Program Modality, and Related Learning Outcomes
The Data Analytics concentration requirements include 1 pre-requisite course to be used as a general elective, 1 fundamental course, 4 required courses and a capstone course, and 2 elective courses, i.e., total of 8 three credit courses (24 credit hours). A listing of the concentration courses is provided in Table 3 and the course descriptions are included immediately thereafter. Computer Applications for Business (BUIS 260) is pre-requisite before beginning the concentration sequence of courses. Other computer science or computer technology courses maybe substituted to satisfy concentration requirements.