Entity-Relationship (ER Modeling) Flashcards
Database Design Process
Requirements Collection & Analysis
Functional & Data Requirements
Conceptual Design
Conceptual Schema
Logical Design
Physical Design
Database designers interview prospective database users to understand and document the data requirements
Requirements Collection &
Analysis
Output of the previous step but we will focus on Data Requirements part of the process
Functional & Data Requirements
Enables database designers to concentrate on specifying the properties of the data without being too concerned with storage and implementation details
Conceptual Design
Output of Conceptual Design
Concise description of the data requirements and includes detailed descriptions of the entity types, relationships, and constraints
Conceptual Schema
Conceptual data model transformed into representational (implementation) data model
Logical Design
Internal storage structures, file organizations, indexes, access paths, and other physical design parameters are specified
Physical Design
Popular high-level conceptual data model
Describes data as entities, relationships, and attributes
Entity-Relationship (ER) Model
Thing or object in the real world with an independent existence
Entity
May be physical existence (e.g. car, employee, student)
May be conceptual existence (e.g. job, course)
Has Attributes
Entity
A particular property that describes an entity
Attribute
Entity vs Entity Type vs Entity Set
Entity - Thing or object in real world
Entity Type - Defines a collection or set of entities that have the same attributes. Describes the schema for a set of entities that share the same structure
Entity Set - Collection of all entities of a particular entity type in the database at any point in time Also called entity collection
Has 1 or more key attributes (Represented as a regular entity using a rectangle)
Strong Entity Type
Has no key attributes, normally has a partial key and is represented using double rectangles
Weak Entity Type
Types of Attributes
Atomic vs Composite
Single-Valued vs Multivalued
Derived vs Stored
Complex
Key
Partial Key
Relationship Attributes
Can be divided into smaller subparts which represent more basic attributes with independent meanings
ex: Name broken down to Fname, Lname, MI
Composite Attributes
Not divisible
Atomic or Simple Attributes
ex: Age
Has single value for a particular
entity
Single-valued
Can have a set of values for the same entity
May have lower and upper bounds to constrain the number of values allowed for each individual entity
Represented by double ovals
Multivalued Attribute
Value determined using other attributes or properties (e.g. count)
Represented by dashed oval
Derived Attribute
Opposite of derived attribute
stored attribute
Nesting of composite and/or multivalued attributes
Complex Attributes
Attribute whose values are distinct for each individual entity in the entity set
Attribute name underlined with a solid line
Key Attribute (No primary key concept yet in ER modeling)
TRUE OR FALSE:
Several attributes can (together) form a key; Use composite attribute and designate it as key
TRUE