CS 442: Data Warehousing and Visualization
Credit Hours: (4)
Prerequisites: CS 340 with a grade of “C” or better and STAT 200 or STAT 301.
Advanced examination of the principles of database systems to support analytical applications, studying and practicing techniques for modeling, managing, analyzing, and visualizing large data sets. Explores traditional and cloud-based software architectures for implementing the entire business intelligence pipeline: ETL process, data quality, dimensional modeling, data visualization, and machine learning algorithms. Emphasizes communicating with data (oral and written) to empower data-driven decision making.
Detailed Description of Content of the Course
Topics include:
1. Introduction to business intelligence
2. Data warehousing
3. Data Exploration, Analysis, and Visualization
4. Machine Learning Algorithms
VI. Detailed Description of Conduct of Course:
Blended delivery combines video lectures, online resources, class discussion, and hands-on learning activities. Students use industry-leading tools and one or more enterprise level database management systems to explore, analyze, manage, process, and visualize data.
Student Learning Outcomes
Students who complete the course will be able to:
Assessment Measures
A significant component of the assessment must measure each individual student’s mastery of the conceptual and applied knowledge and skills described in the course objectives. Evaluations may include but are not limited to assignments, projects, papers, presentations, quizzes, and examinations.
Review and Approval
September 25, 2001 New course proposal John P. Helm, Chair
October 26, 2007 Update Art Carter, Chair
November XX, 2010 Update Art Carter, Chair
Revised: June 1, 2012
Revised: 2014
March 01, 2021