This course builds foundational data management skills, focusing on designing, implementing, and strategically using databases to support data-driven and AI-enabled decisions. Topics include data modeling, relational databases, SQL, architecture, storage, and integrity, plus modern challenges involving big data, unstructured data, cloud ecosystems, and AI/ML-integrated tools and practical enterprise use cases.
Athena Title
Database Management
Equivalent Courses
Not open to students with credit in MIST 7600
Non-Traditional Format
This course will be taught 95% or more online.
Semester Course Offered
Offered fall
Grading System
A - F (Traditional)
Student learning Outcomes
Students will understand the organizational issues involved in data management.
Students will develop a valid data model for a business system of medium complexity.
Students will build and use a relational database.
Students will use of AI to Enhance SQL Query and Data Models.
Students will formulate complex relational database queries.
Students will understand the different data storages and recommend one.
Students will understand data integrity and how to maintain it.
Students will discuss issues related to managing "big data."
Students will be familiar with the principles of managing and exploiting organizational data.
Students will explain how data literacy and management support artificial intelligence and machine learning workflows.
Students will apply data governance and ethical data management principles to ensure quality, fairness, and compliance in AI-enabled decision-making systems.
Topical Outline
The organizational perspective on data management.
Data modeling and SQL.
Relational DBMS.
Organizational intelligence technologies.
Data analysis.
Data structure and storage.
Data processing architectures.
Data integrity and data administration.
Data management for AI and machine learning applications.
Ethical and governance considerations in AI-driven data systems.
