Business Data Analytics Minor

School of Business and Economics

Curriculum

  • Business Data Analytics
  • 18 Units
  • BUS 201: Introduction to Management, Marketing, and Information Technology
  • 3

This survey course will look at today's American business systems including a study of various types of businesses and the information they gather, store, and process, including administration and management of people, facilities, and information. Course will include relevant computer experience simulating business situations.

  • BDA 337: Introduction to Business Data Analytics
  • 3

This course will examine how data analysis technologies can be used to improve decision-making through the study of fundamental principles and techniques of data mining using real-world examples, cases, and software to place data-mining techniques in context, to develop data-analytic thinking, and to illustrate that proper application is as much an art as it is a science. Topics will include introduction to data mining, machine learning, and artificial intelligence: concepts and definitions, the data mining process, predictive and descriptive tasks.

  • BDA 338: Big Data Analytical Tools
  • 3

This course will introduce methods, tools, and applications used to extract and analyze big data with a focus on the use of these approaches and instruction on basic programming, design, and critical thinking skills necessary to use the applications. Prerequisites: BUS 201 and BUS 224.

  • BDA 436: Data Visualization
  • 3

Learn how to transform information from a format efficient for computation into a format efficient for human perception, cognition, and communication. Explore elements of computer graphics, human-computer interaction, perceptual psychology, and design in addition to data processing and computation. Learn to present data to an observer in a way that yields insight and understanding. The first part focuses on the infrastructure for data visualization. It introduces elementary graphics programming, focusing primarily on two-dimensional vector graphics and the programming platform for graphics. This infrastructure will also include lessons on the human side of visualization, studying human perception and cognition to gain a better understanding of the target of the data visualization. The second part will utilize the knowledge of graphics programming and human perception in the design and construction of visualizations, starting with simple charts and graphics and incorporating animation and user interactivity. The third part expands the data vizualization vocabulary with more sophisticated methods, including hierarchical layouts and networks. The final part focuses on visualization of database and data mining processes, with methods specifically focused on visualization of unstructured information, such as text, and systems for visual analytics that provide decision support. Prerequisite: BDA 337.

  • BDA 437: Optimization and Decision Analytics
  • 3

This course will introduce quantitative decision making tools. Quantitative decision making adds value to data by using it to build models that can help in the decision making process. Topics covered include property and density estimation, streaming and sampling selection, decision trees, recursive partitioning and Monte Carlo simulation. The focus will be on understanding the intuition behind the solution techniques used in analyzing big data and machine learning, as well as the application of these tools using analytic software packages. Prerequisite: BDA 337 and MTH 265.

  • MTH 265: Introduction to Statistics
  • 3

As a basic statistics course applicable to education, business, and the hard sciences, this course will include topics such as descriptive statistics, the normal, binomial, F-, and Chi-squared distributions, and hypothesis testing. Optional topics might include additional non-parametric tests and ANOVA. A TI-83 graphing calculator or Microsoft Excel is required. Prerequisites: CMTH 101, MTH 201, MTH 252, MTH 271 or equivalent

Current students, please note: The requirements listed here may not reflect the most current courses for this major and may not be the requirements for the catalog year you are following to complete your major. Please refer to the Academic Catalog for official requirements you must meet to qualify for a degree.


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