4.1 Data Models

A Data Model is an abstract model that organizes elements of data and standardizes how they relate to one another and to properties of the real-world entities.

Classification of Data Models:

1. Conceptual Data Models (High-level): Use concepts like entities, attributes, and relationships. (e.g., ER Model).
2. Representational Data Models (Implementation): Used by most commercial DBMSs. (e.g., Relational, Network, and Hierarchical models).
3. Physical Data Models (Low-level): Describe how data is stored as files, including record formats, orderings, and access paths.

4.2 Database Schema vs. Database Instance

It is crucial to distinguish between the "description" of the database and the "data" itself.

4.3 Data Independence

Data independence is the ability to modify a schema definition in one level without affecting a schema definition in the next higher level.

1. Logical Data Independence:

• The ability to change the conceptual schema without changing the external schemas or application programs.
• Example: Adding a new attribute to a table shouldn't break a report that doesn't use that attribute.

1. Physical Data Independence:

• The ability to change the internal schema without changing the conceptual schema.
• Example: Moving the database from one hard drive to another or changing from B-tree to Hashing for an index.