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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