Data modeling is a process of defining and organizing data to represent real-world entities and their relationships in a structured and efficient manner. It’s a crucial step in database design, helping to ensure that the database accurately reflects the business requirements.
Data modeling encompasses various types and approaches, each suited to specific needs and scenarios. Here’s a list of some common types of data modeling:
1. Conceptual Data Modeling:
- Focuses on high-level business concepts and relationships.
- Uses techniques like Entity-Relationship Diagrams (ERD).
- Ignores implementation details.
2. Logical Data Modeling:
- Translates the conceptual model into a more detailed structure.
- Specifies attributes, data types, and relationships.
- Often represented using a Data Definition Language (DDL).
3. Physical Data Modeling:
- Addresses implementation details specific to the database system.
- Includes considerations like indexing, partitioning, and storage optimization.
- Translates logical models into tables, indexes, and other database objects.
