This course surveys the fundamental concepts and theories used in organizing and structuring data that arise in a wide range of contexts (e.g. lab sciences, economic, social services, computing system performance, environmental sustainability). Course topics include data organization theory, basic relational model theory, normalization theory, relational algebra, data quality, data integrity and security, and mapping a data model into a database schema. Students will learn how to construct and use databases while maintaining the security and integrity of data as well as develop AI literacy in the context of data model design, learning how to apply and critique Artificial Intelligence responsibly and ethically. Hands-on assessments are included in this course.