AI Academic Platform ERD with Legacy Vector System
About This Architecture
Comprehensive entity-relationship diagram for an AI-powered academic platform integrating user management, course structure, collaborative messaging, and a legacy vector system on OCI infrastructure. The schema spans 13 core tables—Semester, Subject, User, Material, Activity, Conversation, Message, Document_File, Feedback, and supporting entities—with foreign key relationships enabling role-based access control and audit trails. This architecture supports instructor-student enrollment, material versioning, AI-driven conversations with document context, and message feedback loops, addressing the need for scalable, auditable learning environments. Fork and customize this ERD on Diagrams.so to adapt table structures, add indexes, or integrate additional OCI services like Autonomous Database or Object Storage. The legacy vector system section indicates planned migration or coexistence with embedding-based retrieval, a common pattern for AI-enhanced educational platforms.
People also ask
How do I design a database schema for an OCI-hosted academic platform that supports instructors, students, course materials, AI-driven conversations, and legacy vector embeddings?
This ERD provides a production-ready schema with 13 core tables including Semester, Subject, User, Material, Conversation, Message, and Feedback, connected via foreign keys to enforce referential integrity and enable role-based access. The design supports multi-tenant enrollment, audit trails through Activity logging, document versioning, and a legacy vector system section for embedding-based retr
- Domain:
- Data Engineering
- Audience:
- Database architects and backend engineers designing multi-tenant academic platforms on OCI
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