Database Design and Data Modeling (DAX511) - This course will investigate principles and practices of database management and design. Student will compare and contrast relational database design, normalization, SQL queries, reports and other interfaces to database data, and documentation. Examination of public sources of data will lead to the practice of applying data sources in real-world examples. This course will utilize spreadsheet (i.e. Microsoft Excel) and database (i.e. Microsoft Access) technology currently used in organizations by applying functions in key field areas such as pivot tables, charts, queries, reports, macros, data load utilities, records and modules.
Applied Statistics for Data Analytics (DAX521) - This course will explore techniques to analyze data, produce graphical illustrations and draw conclusions using statistical, data analysis and visualization software packages. Focusing on the central tendency, data exploration and analytics, probability distributions and random variables, students will compare and contrast the basics of statistical inference, testing hypothesis and building confidence intervals, correlation and causation, and simple and multiple regression analysis.
Advanced Data Analysis Techniques (DAX631) - This course prepares students for analyzing data using advanced data analysis software and techniques to make decisions on data. Topics include Multivariable Regression, Non-Linear Regression, ANOVA, Cluster and Factor Analysis and Logistics Regression.
Data Visualization, Design and Presentation (DAX641) - This concentration capstone course will synthesize the previous learning outcomes in the Data Analytics Concentration to compose and construct a final project demonstrating application of data presentation and design. The design of the final project will focus on visualizing data analysis in real-world application by combining techniques of data modeling and data analytics; data processing; mapping data attributes to graphical attributes; and, constructing strategic visual encoding based on known properties of visual perception. Additionally, students will justify the effectiveness of visualization designs and critical thinking necessary in design decisions. Students will create their own data visualizations, and learn to use visualization tools and software.