Introduction To Data Model Computer Science Essay

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An important aspect of most all business is record keeping and In our information society, this has become an important aspect of business, and it is use as a plan for developing applications, especially how data is store and access. A data model is independent of hardware, software constraints. Rather than try to represent the data as a database would see it, the data model focuses on representing the data as the user sees it in the "real world" and it serves as a bridge between the concepts that make up real-world events and processes and the physical representation of those concepts in a database. In the data manage system, the data model introduce various new ways of how to organizing data. Data models are that can be understood through the flowchart as well as it illustrate the relationship between data. A database can have various types of data models. There are,

Hierarchical data model

Network data model

Relational data model

Object relational data model

Object oriented data model.

All of this data models are use various methods to represent relationship between their data in the data base. As well as all of system designer and the programmers must understand about those methods. Therefore they can identify all of problems in the data where in the file and data base. After the identifying those problem and they can correct and redesign all of them

Hierarchical data model

In this hierarchical data model is, all of the data are organize like a tree structure. Actually it is a hierarchy of parent and child data segment and in this structure, record can have repeating information. At the top of this hierarchical model is a single record. Within hierarchical model, create a link between record types. It uses parent child relationships. In this method, it uses 1: N mapping between record types. As well as one parent can have many child. But one child cannot have many parents. Actually in this structure, in each phase represent the collection of the data about as a single subject. The system analysts can use lines, to show connection between the parent and children. Hierarchical DBMSs were popular from the late in 1960s.

Structure of Hierarchical Data Model

1.1.1.1. Advantages of Hierarchical model

Simplicity:  Then the database is based on the hierarchical structure, the relationship between the different layers is logically simple.

Data Security :The Hierarchical model was the first database model that offered the data security that is provided by the DBMS

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

(5) Efficiency: In this case it is very efficient as when database contains a various 1: N relationship and when the user needs large number of operation.

1.1.1.2. Disadvantages of Hierarchical model:

(1). Implementation complexity - Always it is very easy to design but when we going to implement it, it will be complex one.

(2). Database Management Problem: If you make any changes in the database structure, before you need to make changes in the entire application program that access the database

.

(3). Lack of Structural Independence: there is lack of structural independence because after that we change the structure then it becomes compulsory to change the application too.

(4). Operational Anomalies -When w going to update, delete and add some data, operationally it will be a problem.

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. In 1971, the Conference on Data Systems Languages (CODASYL) formally defined the network model. The basic data modeling construct in the network model is the set construct. 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 multiparent 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 (called junction records by IDMS) may exist, as well as sets between them . Thus, the complete network of relationships is represented by several pairwise sets; in each set some (one) record type is owner (at the tail of the network arrow) and one or more record types are members (at the head of the relationship arrow). Usually, a set defines a 1:M relationship, although 1:1 is permitted. The CODASYL network model is based on mathematical set theory. 

Relational Model

(RDBMS - relational database management system) A database based on the relational model developed by E.F. Codd. 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 organised in tables. A table is a collection of records and each record in a table contains the same fields. 

Properties of Relational Tables:

ï‚· Values Are Atomic

ï‚· Each Row is Unique

ï‚· Column Values Are of the Same Kind

ï‚· The Sequence of Columns is Insignificant

ï‚· The Sequence of Rows is Insignificant

 Each Column Has a Unique Name 

Certain fields may be designated as keys, which means that searches for specific values of that field will use indexing to speed them up. Where fields in two different tables take values from the same set, a join operation can be performed to select related records in the two tables by matching values in those fields. Often, but not always, the fields will have the same name in both tables. For example, an "orders" table might contain (customer-ID, product-code) pairs and a "products" table might contain (product-code, price) pairs so to calculate a given customer's bill you would sum the prices of all products ordered by that customer by joining on the product-code fields of the two tables. This can be extended to joining multiple tables on multiple fields. Because these relationships are only specified at retreival time, relational databases are classed as dynamic database management system. The RELATIONAL database model is based on the Relational Algebra. 

Object/Relational Model

Object/relational database management systems (ORDBMSs) 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 comple x analytical and data manipulation operations to search and transform multimedia and other complex objects.

As an evolutionary technology, the object/relational (OR) 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 (DDLs) while assimilating new object-management possibi lities. Query and procedural languages and call interfaces in ORDBMSs are familiar: SQL3, vendor procedural languages, and ODBC, JDBC, and proprie tary call interfaces are all extensions of RDBMS languages and interfaces. And the leading vendors are, of course, quite well known: IBM, Inform ix, and 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.

According to Rao (1994), "The object-oriented database (OODB) paradigm is the combination of object-oriented programming language (OOPL) systems and persistent systems. The power of the OODB comes from the seamless treatment of both persistent data, as found in databases, and transient data, as found in executing programs." 

In contrast to a relational DBMS where a complex data structure must be flattened out to fit into tables or joined together from those tables to form the in-memory structure, object DBMSs have no performance overhead to store or retrieve a web or hierarchy of interrelated objects. This one-to-one mapping of object programming language objects to database objects has two benefits over other storage approaches: it provides higher performance management of objects, and it enables better management of the complex interrelationships between objects. This makes object DBMSs better suited to support applications such as financial portfolio risk analysis systems, telecommunications service applications, world wide web document structures, design and manufacturing systems, and hospital patient record systems, which have complex relationships between data. 

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