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Conceptual Data Modeling - Coggle Diagram
Conceptual Data Modeling
Purpose of Conceptual Data Modeling
High-level Representation of Business Concepts
Understanding Business Requirements
Communication with Stakeholders
Foundation for Logical and Physical Design
Entity-Relationship (ER) Model
Entities and Relationships
Entity Types and Attributes
Cardinality and Participation
Keys and Relationships Types
Entity Types
Definition and Characteristics
Entity Identification and Naming Conventions
Entity Types vs. Instance of an Entity
Representing Entity Types in ER Diagrams
Attributes
Definition and Types (Simple, Composite, Derived)
Attribute Domains and Data Types
Cardinality and Nullability
Representing Attributes in ER Diagrams
Relationships
Definition and Characteristics
Relationship Types and Degree
Cardinality and Participation Constraints
Representing Relationships in ER Diagrams
Cardinality and Participation
One-to-One (1:1) Relationships
One-to-Many (1:N) Relationships
Many-to-Many (N:M) Relationships
Mandatory and Optional Participation
Conceptual Modeling Tools
ER Diagrams (Crow's Foot Notation, Chen Notation)
UML Class Diagrams
Data Modeling Software (e.g., ERwin, Lucidchart)
Normalization
Functional Dependencies
Normal Forms (1NF, 2NF, 3NF)
Entity-Relationship to Relational Mapping
Eliminating Data Redundancy
Generalization and Specialization
Inheritance in Conceptual Models
Superclasses and Subclasses
Generalization Hierarchies
Representing Inheritance in ER Diagrams
Aggregation
Combining Entities into Higher-Level Objects
Whole-Part Relationships
Aggregation vs. Association
Representing Aggregation in ER Diagrams
Constraints and Business Rules
Domain Constraints
Key Constraints
Relationship Constraints
Integrity Constraints (Entity and Referential)
Validation and Verification
Reviewing and Refining Conceptual Models
Cross-checking with Business Requirements
Ensuring Consistency and Completeness
Iterative Process of Conceptual Modeling