Types Of Data Models

Published Date: 02 Nov 2017

This is the Documentation report on how to develop the database, and how to use this Database System, what are the techniques they need to follow to handle the Database system in a proper way. This assignment is aimed at justifying the management’s decision of creating a database for their organization.

Task 1.1

Explain what is data model, Evaluate different data models explain why older data models are being replaced by new data model

What is Data Module?

A data model in perspective of Software developer is an abstract model  that documents in order to achieve correct data and which data used to developing application as per, specifically how data are stored and process.

Data Model is Independent of software which data a logical map that represents the inherent properties as well hardware component and machine performance will be consider. The model integrates data elements grouped into records, as well as the association around those records. A data model in software engineering is an abstract model that describes how data are represented and accessed.

Data module generally divided in to two algorithms.

The first model is theory about the formal description of the data's structure and use without any mention of heavy technical terms related to information technology.

The second is occurrence is the application of the data model theory in order to create to meet requirements of some applications such as those used in a business enterprise.

Different Data models

A database model is a theory or specification describing how a database is structured and used. Several such models have been suggested

Types of Data models

There are different types of data models, they are:

Hierarchical Model

Network Model

Relational Model

Object/Relational Model

Object Oriented Model

Semi structured Model

Hierarchical Model

A model of hierarchical database is a in which the data is organized into such as a tree structure. The structure is allows in place of information using parent/child relationships: each parent can have many children, but each child has only one parent as known as a 1-to-many relationship

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Figure 1.1.1

Implying a single upward link in each record to describe the nesting, and a sort field to keep the records in a particular order in each same-level list.

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Figure 1.1.2

Advantage of Hierarchical model:

Simplicity – Since it’s based on hierarchical and relationship between various layers is logically simple

.Data Security: Hierarchical fully secured and provided by the dbms.

Data Integrity: Since model relationship seems like the parent child relationship, there is always strong a link between the parent sector and the child sector under it.

Efficiency: efficient model because when the database contains a large number of one to many (1:M) relationship and when the user have need of large number of transaction.

Disadvantages of Hierarchical model:

Implementation Complexity : It quite difficulty to implement

Database Management Problem: We need to change entire structure of programmer while doing changes in any database structure

.Lack of Structural Independence: there is lack of structural self-determination because when we change the structure then it becomes necessary to modify the application too.

.Operational Anomalies: Hierarchical model suffers from the insert, delete and update anomalies, also retrieval operation is difficult.

Network Model

This model organizes data using two fundamental constructs, called records and sets. Records contain fields, and sets define one-to-many relationships between records: one owner, many members.

A set consists of an owner record type, a set name, and a member record type. A member record type can have that role in more than one set; hence the multi parent concept is supported. An owner record type can also be a member or owner in another set. The data model is a simple network, and link and intersection record types may exist, as well as sets between them. The complete network of relationships is represented by several pair wise sets; in each set some record type is owner and one or more record types are members. A set defines a one to much relationship, although one to one is permitted.

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Figure 1.1.3

Advantage of Network model:

Conceptual Simplicity: Seems like above model (Hierarchy model) model it also simple and easy to implement.

Capability to handle more relationship types: the network model can handle one to one1:1 and many to many N: N relationship.

Ease to access data : easier access than Hierarchy model

Data Integrity: Since it is based on the parent child relationship, there is always a link between the parent segment and the child segment under it.

Data Independence: The network model is better than hierarchical model in case of data independence.

Disadvantages of Network Model:

System Complexity: All the records have to maintain using pointers thus the database structure becomes more complex.

Operational Anomalies: As discussed earlier in network model large number of pointers is required so insertion, deletion and updating more complex.

Absence of structural Independence: there is lack of structural independence because when we change the structure then it becomes compulsory to change the application too.

Relational model

The central data description construct in this model is a relation, which can be thought of as a set of records.

A description of data model is called a schema. In the relational model, the schema for is a database model based on first-order predicate logic. Its core idea is to describe a database as a collection of predicates over a finite set of predicate variables, describing constraints on the possible values and combinations of values.

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Figure 1.1.4

A database based on the relational model developed by E.F. Code. 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.

Properties of Relational tables are:

Values are Atomic.

Each row is Unique.

Column values are of the same kind.

The sequence of columns is insignificant.

The sequence of rows is insignificant.

Each column has a unique name.

Employee Data

E_ID

E_F_Name

E_L_Name

E_Dateof Birth

Department Data

D_ID

Advantage of Relational model

Keys of a Relation: it is a set of one or more columns whose combined values are unique

Primary key: primary key is an attribute Its uniqueness of relation which posses the properties

Foreign Key: foreign Key is an attribute of a table, which refers to the primary key of some other table. Foreign key permits only those values, which appear in the primary key of the table to which it refers.

Advantages of Relational Model: 

Conceptual Simplicity:, Relational model is more easier than others.

Structural Independence: Changes don’t affect to other data sector

Design Implementation: Structure independent and implement easier

Disadvantages of Relational Model: 

Hardware overheads: For data store and database system need more influential hardware computers and data storage devices. Relational database systems hide the implementation complexities and the physical data storage details from the user. For doing this

Ease of design can lead to bad design: the relational model is easier to design and implement. The user requirements not to know the complexities of the data storage. This ease of design and use can lead to the development and implementation of the very poorly designed database management system.

Object/Relational Model

Object/relational database management system (ORDBMS) add new object storage capabilities to the relational systems at the core of modern information systems. These new facilities integrate management of traditional fielded data, complex objects such as time-series and geospatial data and diverse binary media such as audio, video, images, and applets. By encapsulating methods with data structures, an ORDBMS server can execute complex analytical and data manipulation operations to search and transform multimedia and other complex objects.

As an evolutionary technology, the object/relational approach has inherited the robust transaction- and performance-management features of it s relational ancestor and the flexibility of its object-oriented cousin. Database designers can work with familiar tabular structures and data definition languages while assimilating new object-management possibilities.

The extension of ORDBMS languages are:

SQL3

Vendor procedural languages

ODBC

JDBC

Proprietary call interfaces

The leading vendors of ORDBMS are:

IBM

Inform ix

Oracle

Object Oriented 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. A major benefit of this approach is the unification of the application and database development into a seamless data model and language environment. As a result, applications require less code, use more natural data modeling, and code bases are easier to maintain. Object developers can write complete database applications with a modest amount of additional effort.

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Figure 1.1.5/Object Oriented Model

Semi structured Model

The semi structured data model has the information that is normally associated with a plan is contained within the data, which is sometimes called ``self-describing''. In such database there is no clear separation between the data and the schema, and the degree to which it is structured depends on the application. In some forms of semi structured data there is no separate plan, in others it exists but only places loose constraints on the data. Semi-structured data is naturally modeled in terms of graphs which contain labels which give semantics to its underlying structure. Such databases include the modeling power of recent extensions of flat relational databases, to nested databases which allow the nesting of entities, and to object databases which allows cyclic references between objects.

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Figure 1.1.6/ Semi Structured Model

Difference between the Data Models

Network Data Model Vs Hierarchical Data Model

Network Data Model

Hierarchical Data Model

Many to many relationship can be used.

Easily accessed because of the linkage between the information.

Greatly flexible among the information files because of the multiple relationships among the files.

One to many relationship can be used.

Difficult to navigate because of its strict owner to member connection.

Less flexible with the collection of information because of the hierarchical position of the files.

Table 1.1.1/Network Data Model Vs Hierarchical Data Model

RDBMS Vs Network Data Model

RDBMS

Network Data Model

The Relational Model represents data in a tabular format with each row representing an entity of some type, and with each column representing a defining attribute of the entity.

The Network Model commonly represents data and relationship through diagrams containing boxes and arrows.

Table 1.1.2/RDBMS Vs Network Data Model

RDBMS Vs Hierarchical Model

RDBMS

Hierarchical Model

The Relational Model represents data in a tabular format with each row representing an entity of some type, and with each column representing a defining attribute of the entity.

The Relational Model does not any problems with many to one or many to many relationship.

The Hierarchical Data Model organizes the data in a tree structure.

Hierarchical Model has problems with many to one or many to many relationship.