AMS 521, Data Management

This course teaches how to manage databases, covering core concepts such as database architecture, data storage, querying, and transaction management. Students will learn how to design and build databases, work with distributed systems, and manage multiple concurrent processes. Topics include data warehousing, data cleaning, and data mining, with hands-on practice using R and SQL to prepare real-world datasets for analysis. The course also introduces modern database technologies, including graph databases for modeling complex relationships, vector databases for AI-driven similarity search on unstructured data, and AI-powered database management systems that apply machine learning to optimize performance and automate data processing tasks.

Prerequisites:  There are no prerequisites for this course, and we will start learning R and SQL from the very beginning.  However, having some prior experience would be helpful.

3 credits; ABCF grading

Course materials will be supplied by the instructor via Brightspace

Topics:

Students will also explore topics like data warehousing (storing large amounts of data), cleaning data, and data mining (finding useful information from data). The course includes hands-on practice with R and SQL, where students will clean, organize, and combine raw data to prepare it for analysis. This practical experience will help students develop key skills in getting data ready for use in projects.

Learning Outcomes:

By the end of this course, students will understand
--the basics of managing databases, which are important tools for organizations;
--receive practical experience in designing and building databases, cleaning up raw data, and preparing it for analysis using R and SQL.