Data modeling is the first step in creating a database and involves creating a conceptual representation of the required data structures. A data model focuses on what data is needed and how it should be organized rather than operations performed on the data. There are three levels of data modeling: conceptual, logical, and physical. The conceptual model identifies high-level relationships between entities while the logical model describes the data and relationships in detail without regard to implementation. The physical model represents how the data will be implemented in the database. Entities, attributes, relationships, cardinality, and ordination are key concepts in data modeling.

1. DATA MODELING
BASICS

2. What is a Data?
• “Data are values of qualitative or quantitative
variables, belonging to a set of items”

3. What is a set of items?
• “Set of items” means “set of objects you are interested in”

4. What is a variable?
• Variables are a measurement or characteristics of an item

5. Qualitative Vs Quantitative variables?

6. What is a Data Model?
• Data modeling is often the first step in creating a
database
• A data model is a conceptual representation of the data
structures that are required by a database.
• The data structures include the data objects, the
association between data objects
• Data model focuses on what data is required and how it
should be organized rather than what operations are
performed on the data
• Data model is independent of hardware or software
constraints

7. Levels of data modeling:
• There three level of data modeling:
1. Conceptual data model
2. Logical data model
3. Physical data model

8. Conceptual Data Model
• A conceptual data model identifies the highestlevel relationships between the different entities.

9. Logical Data Model
• A logical data model describes the data in as much
detail as possible, without regard to how they will
be physical implemented in the database.
• Identify entity and relationships.
• All attributes of each entity.
• Identify primary and foreign key.

10. Physical Data Model
• Physical data model represents how the model will
be built in the database.

12. Entity
• An entity is a Person, place, object, event or
concept about which data is to be maintained
• When implementing a database an entity would
transmit to a table

13. Attribute
• An attribute is a property of an entity which
describes the characteristics of a particular entity
instance.
An attribute can be of three types:
a. Unique Identifier: A UID is an attribute whose
value uniquely identifies an entity instance. A UID is
implemented as a Primary Key.
b. Mandatory Attribute: A mandatory attribute is
one whose value cannot be null.
c. Optional Attribute: An optional attribute is one
whose value can be null.

14. Entity Relationship Models
• Cardinality: Cardinality specifies how many
instances of an entity relate to one instance of
another entity
1. One-to-One Relationships
2. One-to-Many Relationships
3. Many-to-Many Relationships
• Ordinality: Ordinality describes the relationship as
either mandatory or optional
1. Mandatory Relationships
2. Optional Relationships
• Recursive Relationships

15. Mandatory, Many-to-Many
INSTRUCTOR
STUDENT

16. Optional, Many-to-Many
DEPARTMENT
STUDENT

17. Optional/Mandatory,
Many-to-Many
INSTRUCTOR
SKILL

18. Optional/Mandatory,
One-to-Many
PRODUCT
VENDOR

19. Mandatory, One-to-One
AUTOMOBILE
ENGINE

20. Recursive
EMPLOYEE
is supervised by
supervises

21. Resolving Many-to-Many Relationships
• Many-to-many relationships should be avoided. We
can resolve a many-to-many relationship by dividing it
into two one-to-many relationships.

22. Resolving Many-to-Many Relationships
SALES ORDERS
SALES ORDERS
INV. ITEMS
ORDER ITEMS
INV. ITEMS

23. CUSTOMERS
SALES ORDERS
ORDER ITEMS
INV. ITEMS