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INFO MANAGEMENT L3

Entity Relationship Modeling

QuestionAnswer
a conceptual model for designing a databases. This model represents the logical structure of a database, including entities, their attributes and relationships between them. The Entity-Relationship Model (ER Model)
a conceptual approach to designing databases by identifying the entities, attributes, and relationships between data objects. It provides a visual blueprint of how data interacts within a system before actual database creation. Entity Relationship Modeling (ER Modeling)
Purpose of ER Modeling: To help analyze and structure data To serve as a communication tool between developers To create a foundation for relational database design
A person, place, thing, or event that an organization wants to store data about. Entity
A characteristic or property of an entity. Attribute
An association between two or more entities. Relationship
defines how many instances of one entity are related to instances of another entity. Cardinality
Unique identifiers that distinguish records Keys
uniquely identifies each entity Primary Key
links related entities Foreign Key
Examine the business requirements (rules) to identify the main nouns or concepts about which data must be stored Identify Entities (The Nouns)
Define the attributes (data fields) that describe each entity Define Attributes (The Properties)
The resulting ER Diagram visually confirms the database structure. Establish Relationships and Cardinality (The Verbs and Rules)
Shows how entities and relationships CONNECT IN AN EASY TO UNDERSTAND DIAGRAM. Helps both technical and non-technical users visualize database structure. Clear Data Visualization
Acts as a common language between system analysts, developers, and end-users. Ensures everyone understands how DATA FLOWS THROUGH THE SYSTE, Improves Communication
Identifies entities, attributes, and relationships BEFORE IMPLEMENTATION. Minimizes data redundancy and ensures consistency Efficient and Accurate Design
DETECT THE DESIGN ISSUE early in the planning stage, saving time and effort. Early Error Detection
ER Models can be systematically converted into relational database tables Easy Transition to Database
ER Models describe what data exists, not how it is processed or used. Cannot show workflows or system behavior. Focuses Only on Structure
Poor at capturing complex rules (e.g., time-based conditions or business constraints).Such logic must be handled by the application layer. Limited Expressiveness
Diagrams become cluttered and hard to interpret when too many entities exist. Complexity in Large Systems
Different designers may model the same system differently (Entity vs. Attribute confusion). Subjective Design Choices
Works best for structured, relational databases — not for big data, multimedia, or NoSQL systems. Not Ideal for Unstructured Data
Created by: user-1782765
 



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