Week 4 notes

Process Modeling

• Definition:

  • A graphical representation of processes that capture, manipulate, store, and distribute data.

  • Helps in understanding data flow between systems and components.

  • Utilizes information gathered during requirements determination.

• Common Methods Used in Process Modeling:

  • Data Flow Diagram (DFD)

  • Entity Relationship Diagram (ERD)

2. Entity Relationship Diagram (ERD)

• Definition:

  • A diagram that illustrates how entities (e.g., people, objects, or concepts) relate to each other within a system.

• Purpose:

  • Used to model relational databases.

  • Helps in defining business logic.

  • Acts as an initial step in database design.

Benefits of ERDs:

• Provides a conceptual data model.

• Helps in understanding business rules.

• Can be translated into relational tables.

3. Components of ERDs

• Entities: Represent real-world objects (e.g., Employee, Car, House).

• Attributes: Define the properties of an entity (e.g., EmpName, EmpAddr, EmpJob).

• Primary Keys:

  • Uniquely identifies an entity.

  • Should be stable and unique (e.g., EmpID instead of EmpName).

  • Steps to define a Primary Key:

    1. Select an attribute.

    2. Underline it in the ERD.

• Relationships:

  • Defines the association between entities.

  • Can be Unary, Binary, or Ternary.

  • Example: A "Student" lives in a "Residence Hall."

4. Relationships in ERDs

• Degree of Relationship:

  • Unary: An entity is related to itself (e.g., "Employee manages Employee").

  • Binary: A relationship between two entities (e.g., "Student enrolls in Course").

  • Ternary: A relationship involving three entities.

• Cardinality:

  • Defines how many instances of one entity relate to another.

  • Common values:

    • 1:1 (One-to-One)

    • 1:M (One-to-Many)

    • M:N (Many-to-Many)

  • Example:

    • 1:M: A customer places multiple orders.

    • M:N: Students enroll in multiple courses.

• Multi-Valued Attributes:

  • Attributes that have multiple values for a single entity.

  • Example: An "Employee" can have multiple skills.

  • Fix: Convert them into a new entity.

5. Database Business Rules

• Define constraints and conditions that must be followed.

• Examples:

  • Online Gambling System: Must not accept users from locations where gambling is illegal.

  • Banking System: Declines purchases if insufficient funds.

  • Beer Information System: Must verify age (21+) before allowing a purchase.

6. Modeling Hints & Real-World Examples

• The Marathoner Example:

  • A database tracks marathon runners and race performances.

  • A race has many participants.

  • Professional runners are uniquely identified.

• Laboratory Example:

  • Tracks chemists, projects, and equipment usage.

  • Captures details such as chemist names, project IDs, and equipment costs.

• Vendor & Production Example:

  • COO manages production runs.

  • Materials have preferred vendors and contract pricing.