Based on: Database Design - 2nd Edition covers database systems and database design concepts. New to this edition are SQL info, additional examples, key terms and review exercises at the end of each chapter.
The picture of you, not of the topic. Each statement is something you'll be able to do by the end.
I can Distinguish and Evaluate Data Storage Methods
I can Design and Implement Database Schemas
I can Perform and Optimize Database Operations
I can Analyze and Apply Database Constraints and Dependencies
The path through the material. Each lesson tackles one essential question.
What makes a database the right tool for shared, concurrent data work compared to ad hoc file systems?
How do formal rules and precise data definitions let us infer how attributes constrain one another?
How can a table’s definition itself enforce integrity so that bad data cannot enter in the first place?
How do we translate a real-world story into a precise structure that a relational database can store and trust?
What defining qualities distinguish a true database from other ways we store and retrieve information?
How do functional dependencies reveal hidden structure and guide normalization decisions?
How do relationship rules such as cardinality, connectivity, and participation determine whether a design preserves consistency or invites anomalies?
How does a self-describing DBMS with defined user roles turn shared data from a file store into a secure, reliable platform for applications?
How do we turn stakeholder language into an ERD that captures entities and relationships clearly, and reshape many-to-many facts into workable tables?
How do keys and declarative constraints embody business rules, maintain referential integrity, and adapt safely as the schema changes over time?
How does systematic normalization transform a conceptual model into tables that eliminate redundancy and update anomalies while preserving all information?
How does thinking across abstraction levels help translate concepts into a robust BCNF schema that avoids anomalies?
What commitments do different data models and DBMS architectures make, and how do those choices shape conceptual design?
What habits make basic SQL statements a safe, precise way to manage tables and change rows?
Why does understanding relationships let us write queries that combine tables and act precisely on related rows?
How do we prepare and shape data so SQL can reveal patterns at the right level of detail?
Three ways to connect: Claude Code (PAT + install command), Claude Desktop (.mcpb download — no token to paste), or Claude web (Customise → Connectors → Add custom connector, OAuth). Same MCP endpoint, same identity on every path.
https://nebular.live/api/v1/mcp/