Transcript S7

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 Importance
•Data modeling is probably the most
intensive and time consuming part of the
development process
•Building a database without a model is like
building a house without plans
Data Models
•Because the data model uses easily
understood notations and natural language it
can be reviewed and verified by end-users
•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
* Object-Relational Model
* NoSQL Model
* XML 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
User A1
Language
Workspace
User A2
User B1
Language
Workspace
Data Base Administrator (DBA)
*
Language
Workspace
Ext. External
Schema A Model A
Ext./Con.
Mapping A
Conc.
Schema
User B2
Language
Workspace
User B3
Language
Workspace
.
*
Ext. External
Schema B Model B
Conceptual
Model
Ext./Con.
Mapping B
DDMS
*
User interface
Inte.
Schema
Stored database (Internal Model)
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
end