Database design and modeling involve creating a structured framework for storing and organizing data. Here are some key concepts and steps in the process:

1. Requirements Gathering: Understand the data needs of the application or organization. This involves discussing with stakeholders to identify what data needs to be stored and how it will be used.

2. Conceptual Design: Create a high-level data model, often using Entity-Relationship (ER) diagrams. This step outlines the main entities (e.g., customers, orders) and their relationships.

3. Logical Design: Convert the conceptual model into a logical model, often using a relational database schema. Define tables, columns, and relationships more precisely.

4. Normalization: Apply normalization rules to reduce data redundancy and improve data integrity. This involves organizing tables and columns to minimize duplicate data and ensure that dependencies are properly enforced.

5. Physical Design: Design how the data will be physically stored in the database. This includes indexing strategies, storage requirements, and performance considerations.

6. Implementation: Create the database schema in a database management system (DBMS) based on the physical design. This step involves writing SQL scripts to create tables, relationships, and constraints.

7. Testing and Validation: Ensure that the database meets the requirements and performs as expected. This involves testing queries, data integrity, and performance.

8. Maintenance and Evolution: Regularly update the database schema as requirements change and optimize performance as needed.

Would you like to dive deeper into any of these steps or need help with a specific aspect of database design?