1. Data Models

2. A description of a database is known as Schema.
What is Schema ???
A description of a database is known as Schema.

3. What is Instance ???
Record at a particular moment of time in a database is known as Instance.

4. What is Data Model???
A data model is an abstract model that describes how data is represented and accessed.

5. Meanings of Data Model
Data Model Theory
Data Model Instance

6. A formal description of how data may be structured and accessed
Data Model Theory
A formal description of how data may be structured and accessed

7. Components of Data Model Theory
Structural Part (data structure used to create databases
representing entities or modeled by database
using create command )
Integrity Part
(rules governing the constraints placed on these
data structures like applying constraints
such as primary key , foreign key)
Manipulation Part
(a collection of operators used to
manipulate the database using queries
and update command)

8. Example of Relational Model
Structural Part (based on modified concept of mathematical
relation)
Integrity Part
(by using first order logic)
Manipulation Part
(using relational algebra , tuple calculus
and domain calculus)

9. Data Model Instance
Data Modeling is the process of creating a data model instance by applying a data model theory.

10. It involves structuring and organizing the data.
Data Modeling
It is a process of creating a data model by applying data model theory to create a data model instance.
It involves structuring and organizing the data.

11. High Level (Conceptual Schema) Low Level (Physical Schema)
Types of Data Model
High Level (Conceptual Schema)
Low Level (Physical Schema)
Representational Data Model
Hierarchical
Relational
Networked
( Logical Schema )

12. Conceptual Schema
It is used to describe the semantics of a domain, being the scope of the model. It consists of Entity Classes and relationships among these entities.

13. Logical Schema
It describes the semantics as represented by the particular data manipulation technology. It consists of description of tables , columns object oriented classes etc.

14. Physical Schema
It describes the physical means by which data is stored. It is concerned with partitions , table spaces etc.

15. Zachman Framework Contextual List (List of Important Things)
Conceptual Model (Entities & Relationships)
Logical Model (attributes & identifiers)
Physical Model (keys , storage requirements)
DDL (Configuration Listing)
Data Instances (Operations Storage)
Zachman Framework

16. What is Logical Data Model???
A data model is an abstract model that describes how data is represented and accessed.

17. Graphical Representations of the business requirements
Contains the things of importance in an organization and how they relate to one another
Contains business textual definitions and examples
Validated and approved by a business representative
Basis of Physical Database design

18. Logical Data Model Vs Physical Data Model
Includes Entities ,attributes and relationships
Includes tables,columns,keys,data types,validation rules,database triggers stored procedures and access controls
Uses business names for attributes
Uses column names limited by DBMS
Is independent of technology
Includes Primary key and indices for fast data acces

19. Is normalized to 4th Normal Form.
Can be de normalized to meet performance requirements
Does not include any redundant or derived data
May include redundant columns
Business subject matter experts validate and approve the model
Physical modeler lead the modeling activity

20. Why build Logical Data Model???
Helps common understanding of business requirements
Provides foundation for designing a database
Facilitates data re use and sharing
Decreases development and maintenance time and cost
Confirms a logical process model and helps impact analysis

21. Logical Modeling Benefits
Clarifies functional specifications and avoid assumptions
Confirms Business requirements
Facilitates business process improvement
Decreases system development time and cost
Data re-using and sharing
Gathers Metadata

22. 3 Schema Architecture of DBMS
View 1
View 2
High Level DM
Representational DM
High Level DM
Conceptual Layer
Internal Layer
Low Level DM

23. What is Data Independence???
It is a capability to change a specific layer without affecting the other two layers.

24. Types of Data Independence
Logical Data Independence
Physical Data Independence

25. Logical Data Independence
The capability to change a conceptual layer without affecting the other two layers

26. Physical Data Independence
Capability to change physical layer without affecting the other two layers

27. It is database model proposed by Dr. E F Codd.
Relational Data Model
It is database model proposed by Dr. E F Codd.
Core idea is to organize data into tables rows and columns). Follows simple concept of relational algebra

28. Networked Data Model
It is a database model conceived as a flexible way of representing objects and their relationships. It was invented by
Charles Bachman.
NM allows each record to have multiple parent and child records forming a lattice structure.

29. Hierarchical Data Model
Data is organized in a tree like structure. It allows repeating information using parent/child relationships.
Each parent can have multiple child but each child has single parent. It uses 1:N mapping also known as one to many relationships.

30. Object Oriented Data Model
Data and associated operations are represented by objects. An object is an identifiable entity with some characteristics and behavior.

31. What Is Relation ???
A relation is defined as a set of n tuple (rows) which stores the data logically in a 2-D format in forms of rows and columns.

32. Relation : Employee
Attributes : Emp_id , ename , designation ,dept
Emp_id
ename
designation
dept
E001
Raghav AM
Civil
E002
Smriti
MANAGER HR
E003
Ashwin DM
Finance

33. Relational Algebra
Projection
Selection
Union
Intersection
Difference
Cartesian Product

34. Two relations A and B are said to be union compatible if and only if
Union Compatibilty
Union Compatible relations are those relations which have same domain and degree.
Two relations A and B are said to be union compatible if and only if
Deg(A)=Deg(B)
Dom(a1)=dom(b1)
Dom(a2)=dom(b2) ..
Dom(an)=dom(bn)

35. Cardinality
No of rows in a relation.

36. One to one (1 : 1) One to many (1 : M) Many to many (M:N)
Cardinality Ratio
One to one (1 : 1)
One to many (1 : M)
Many to many (M:N)

37. Referential Integrity Key Constraints.
Types of Constraints
Entity Integrity
Referential Integrity
Key Constraints.

38. Types Of Key Constraints
Super Key
Candidate key
Primary Key
Alternate Key
Foreign Key

39. A super key is written as a finite set of attribute names.
A super key K holds in a relation (H,B) if:
K is proper subset of H and
There exists two distinct tuples t1 and t2 which must hold the condition
T1[k] = t2[k]

40. Data Modeling Techniques
ER diagrams
EER diagrams
OMT

41. E R Diagram
Works_in
Department
Employee

42. Single Valued / Multivalued Stored and Derived
Types of Attributes
Atomic and Composite
Single Valued / Multivalued
Stored and Derived

43. Types of Entities
Strong Entity
Weak Entity

44. Types of Participation Constraints
Total Participation
Partial Participation

45. Example Database Customer(Customer_id,Tax_id,Name,Address,City,State,
Zip,Phone)
Order(Orderno,Cust_id,invoice_no,date placed,date promised,terms,status)
Order Line(Orderno,Orderlineno,product code,qty)
Invoice(Invoice_no,Cust_id,Order_no,date,Status)
Invoice Line(Invoiceno,lineno,product_code,qty,shipped)
Product(Product_code,prod_desc)