INFORMATIONAL MODEL

 A. INFORMATIONAL MODEL

• An Informational Model, or Information Model, is a conceptual representation of information, data, and their interactions within a domain or system. It establishes a systematic framework for comprehending and arranging data items and their interactions. Database design, system analysis, and knowledge representation all make use of information models.

• In the Informational Model:

• Data elements are classified into entities, characteristics, and relationships.
• Entities are the primary items or concepts inside a domain.
• Attributes describe an entity's traits or properties.
• Relationships describe how entities are related to one another.
• Information models can be represented using a variety of methodologies, including Entity-Relationship Diagrams (ERDs), Unified Modeling Language (UML) diagrams, and domain-specific languages.

B. DATA MODEL

• A data model is a conceptual representation that defines the structure, relationships, and constraints of data within a database system, facilitating the organization and manipulation of information to meet the requirements of an organization or application.

C. NETWORK MODEL

• The Network Model is a database model that stores data as a collection of records, each with many parent and child records, resulting in a network-like structure.

 

D. RELATIONAL MODEL

• The Relational Model is a database model based on the mathematical idea of relations. Data is structured into tables (relations) made up of rows (tuples) and columns (attributes). 

HIERARCHICAL MODEL

• The Hierarchical Model is a database model that arranges data in a tree-like structure, with each record (node) having one parent record (excluding the root record) and potentially several child records. In this paradigm, data is represented as a sequence of parent-child connections, with each child record reporting to its parent record. This paradigm is frequently used to describe data that has a clear hierarchical relationship, such as organizational hierarchies or file systems. When modeling complicated data relationships, it may be less flexible than alternative models, such as the relational model.