Welcome: To the fifth learning sequence “ Data Models “ Recap : In the previous learning...

Welcome: To the fifth learning sequence

“ Data Models“

Recap : In the previous learning sequence, we discussed The Database concepts.

Present learning: We shall explore the following topic:

- The most common types of data models.

Data Models

The goal of the data model is to make sure that the all data objects required by the database are completely and accurately represented.

Data Models

Why is data model important? - -Data modeling is probably the most

intensive and time consuming part of the development process.

- -A common response by practitioners who write on the subject is that you should no

more build a database without a model than you should build a house without blueprints .

Data Models

Because the data model uses easily understood notations and natural language it can be reviewed and verified as correct by

the end-users.

The data model is also detailed enough to be used by the database developers to use as a blueprint for building the physical

database .

Data Models

The information contained in the data model will be used to define the relational tables primary and foreign keys stored procedures and triggers . A poorly designed database

will require more time in the long-term .

Data Models

Model : as description or analogy used to visualized something that be directly observed.

Data model: a collection of concepts that can be used to describe the structure of a database provides the necessary means to achieve this abstraction, by structure of a database , we mean the data types , relationships , and constraints that should hold for the data . Most data models also include a set of basic operations for specifying

retrievals and updates on the database.

Data Models

Some types of data model:

Hierarchical Model *

Network Models *

Relational Models *

*Object-Oriented Model

Data Models

The hierarchical data models organizes data in a tree structure .

There is a hierarchy of parent and child data segments, this structure implies that a record can have repeating information, generally in the child data segments, data in a series of records, which have a set of field values

attached to it.

Data Models

Network data model :

The popularity of the network data model coincided with the popularity of the

hierarchical data model .

Some data were more naturally modeled with more than one parent per child, so the network model permitted the modeling of

many -to-many relationships in data .

Data Models

Relational data model:

A relational database allows the definition of data structures, storage and retrieval operations and integrity constraints, in such a database the data and relations between them are organized in tables. A table is a collection of records and each record in a

table contains the same fields .

Data Models

Object-Oriented data Model: Object DBMSs add database functionality to object programming languages, they bring much more than persistent storage of

programming language objects .Object DBMSs extend the semantics of the C++ , smalltalk and java object programming languages to provide full-featured database programming capability, while retaining

native language compatibility.

Data Models

The American National Standards Institute / Standard Planning And Requirement Comment (ANSI / SPARC) define 3 degrees

of abstraction as illustrated in Figure 1 .

Data Models

The architecture is divided in to three general levels:

1 -External levels

This level is concerned with the way in which the data is viewed by individual users i.e (logical storage).

2 -Internal levels

This level is concerned with the way in which the data is actually stored i.e (physical storage).

3 -Conceptual level

It is the level of indirection between the other two levels (External & Internal levels).

ANSI/SPARC

Language Workspace

Language Workspace

Language Workspace

Language Workspace

Language Workspace

User A1 User A2 User B1 User B2 User B3

ExternalModel A

ExternalModel B

ConceptualModel

DDMS

Stored database (Internal Model)

.

Ext./Con.Mapping A

Ext./Con.Mapping B

Con./Int.Mapping

Ext.Schema A Ext.

Schema B

Conc.Schema

Inte.Schema

Data B

ase Adm

inistrator (D

BA

)

* *

*User interface

Fig.1: An Architecture for Database System

ANSI/SPARC- -Each user of a database system has a language of his or

her disposal. What is important about the used language is that it will include a Data SubLanguage (DSL), which is that subset of the language concerned with database objects and operations.

- -Any given DSL is really a combination of: 1 -Data Definition Language DDL, when provides for the

definition of a database objects. 2 -Data Manipulation Language DML, which supports the

manipulation or processing of those objects. 3 -Structured Query Language SQL, which supports

displaying and retrieving database objects. -Each user provided with a workspace, which acts as

receiving or transmitting area between the user and the database .

ANSI/SPARC-The user is said to view the database by means of an

external model. Each external model is defined by means of an external schema, which consists of description each of the various types of external record in that external model.

-The conceptual model is a representation of the entire information of the database, which defined by means of the conceptual schema, that includes definitions of various types of conceptual record.

-The internal level consists of multiple occurrence of multiple type of stored records, and is described by means of internal schema, which also specifies what indexes

exists, and how stored fields are represented, and so on .

Data Models

Categories of data models:

Conceptual data models : these models, sometimes called domain models , are typically used to identify and document business (domain) concepts with project stakeholders. Conceptual data models are often created as the precursor to logical data

models (LDMs) or as alternatives to LDMs .

Data Models

Logical data models (LDMs) : logical data models are used to further explore the domain concepts, and their relationships and relationship cardinalities. This could be done for the scope of a single project or for your entire enterprise. Logical data models depict the logical entity types, typically referred to simply as entity types, the data attributes describing those entities, DDL can be

generated at this level .

Data Models

Physical data models (PDMs) : physical data models are used to design the internal schema of a database, depicting the data tables (derived from the logical data entities), the data columns of those tables (derived from the entity attributes), and the relationships between the tables derived

from the entity relationships .

Data Models

Major event in data model include:

-Identifying the data and associated processes.

-Defining the data (such as data types , sizes , and defaults).

-Specifying data storage requirements.

-Defining the data management processes (such as security reviews and backups.

-Ensuring data integrity (by using business rules and validation checks) .

Data Models

Summary: In this learning sequence, we discussed the best common types of data

models.

Data Models

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