A PROJECT ON Analysis and Development of a Pay Per Click Advertising System : Chapter Three

Chapter 3 PHP & Database Management System & Its Application 1. PHP and its Application 2. Database and its Application 3. Data Modelling 3.1 PHP and Its Application PHP (recursive acronym for "PHP: Hypertext Pre-processor") is a widely-used Open Source general-purpose scripting language that is especially suited for Web development and can be embedded into HTML (Hyper Text Mark-up Language). Five important characteristics of PHP are: • Familiarity: Programmers from many backgrounds will find themselves already accustomed to the PHP language as many of the language’s constructs are borrowed from C and Perl. • Simplicity: A PHP script can consist of 10000 lines on one line; there is no need to include libraries, especial complication directives or anything if sort. • Efficiency: Efficiency is an extremely important for working in a multi-user environment such as the WWW. It introduces resource allocation mechanisms and more pronounced support for object-oriented programming, in addition to session management features. • Security: PHP provides developers and administrators with a flexible and efficient set of security safeguards. These safeguards can be divided into two frames of references: 1. System level safeguards 2. Application level safeguards • Flexibility: Because PHP is an embedded language, it is extremely flexible towards meeting the needs of the developer. Although PHP is generally touted as being used in conjunction solely with HTML, it can also be integrated alongside language like JavaScrit, XML etc. A wisely planned PHP application can be expanded as needed. In technical terms, PHP is a cross-platform, HTML-embedded, server-side web scripting language. • Cross-platform: We can run most code, without alteration, on computers running many different operating systems. • HTML-embedded: PHP code is written in files containing a mixture of PHP instructions and HTML code. • Server-side: The PHP programs we write are run on a server- specifically, a web server. • A web scripting language: we run PHP programs via a web browser. We access the web server on which they reside, and this runs the program, sending any resulting output back to the browser. This figure shows how PHP work : Web Server Fetch page Figure 3.1 How PHP Works. 3.2 Database and Its Application: Database systems are designed to manage large bodies of information. Management of data involves both defining structures for storage of information and proving mechanisms for the manipulation of information. In addition, the database system must ensure the safety of the information stored, despite system crashes or attempts to unauthorized access. If data are to be shared among several users, the system must avoid possible anomalies results. 3.2.1 Definition and Concept of Database DBMS stands for Data Base Management System and is defined by its ability to store, retrieve and manipulate information. In the simplest form, a computer's operating system filing capabilities can be considered a DBMS. A database management system (DBMS) consists of a collection of interrelated data and a set of programs to access those data. The collection of data is usually referred to as the database, consists of information relevant to an enterprise. The primary goal of DBMS is to provide an environment that is both convenient and efficient to use in retrieving and storing information [3]. Database systems are designed to manage large bodies of information. The management of data involves both definition of structures for storage of information and the provision of mechanisms for the manipulation of information. In addition, the database system must provide the safety of information stored, despite system crashes or attempts of unauthorized access. Advantages of Database System: 1. Several important advantages of database systems are listed below [1]. 2. Redundancy can be reduced 3. Inconsistency can be avoided. 4. The data can be shared 5. Standards can be enforced 6. Security restrictions can be applied 7. Integrity can be maintained 8. Conflicting requirements can be balanced 3.2.2 MySQL MySQL is an open source, SQL Relation Database management system (RDBMS) that is free for many uses. Early in its history, MySQL occasionally faced opposition due to its lack of support for some core SQL constructs such as sub selects and foreign keys. MySQL has not failed to reward the loyalty of these users with the addition of both sub selects and foreign keys. 3.2.3 Database System versus File System The typical file processing system is supported by a conventional operating system. The system stores permanent records in various files and it needs different application programs to extract records from it and add records to the appropriate files. Before database management system came along, organization usually stored information/data in such system. Keeping data/information in file processing system has a number of major disadvantages: o Data redundancy and inconsistency o Difficulty in accessing data o Data isolation o Integrity problem o Atomicity problem o Integrity problem o Concurrent access anomalies o Security problems These difficulties, among others, prompted the development of the database. 3.2.4 Information Modelling Whenever understanding of a real world phenomenon or interaction is desired the first step is to build a simple model representing the phenomenon and perform study and evaluation of the model rather that actual interaction. In building model the ambiguity and complexity in the real world is avoided totally or compensated with valid approximation. In fact a systematic study of any phenomenon whether economic, industrial or scientific is done through modelling. Information modelling pertains to development of model in information generation, storage, destruction, evaluation, manipulation, synthesis and utilizations. These models help in systematisation of information generation, flow, interpretation and synthesis of more information. 3.2.3.1 Concept of Information Modelling The first step of information modelling is to precisely choose only that part of reality, which is of interest. This is known as Entity. Entity defines other parameters. Entities are atomic i.e. they are invisible. The parameters if as entity are known as attribute. Attributes are quantum of information, which describe the entity entirely. Attributes themselves can be thought of entities, which make the first entity of a composite entity. The key attribute if one, which distinguishes one occurrence if an entity from other. It is associated with all other attributes with a 1:1 (one-to-one) relation. The second step in information modelling is relationship among entities. It is most important in making sense if the entity and inter-entity relationship. The relationship is the information, which links two entities. The relationship can be of four categories:  One-to One (1:1) - One instance of the first entity can correspond to only one instance of the second entity. It is also known as binary relationship.  One-to-Many (1:N) - One instance of the first entity can correspond to more than one instance of the second entity.  Many-to-One (N:1) - More that one instance of the first entity can correspond to the same one instance of the second entity.  Many-to Many (N:N) - More that one instance of the first entity can correspond to more than one instance of the second entity. In information modelling, One-to-One (1:1) and One-to-Many (1:N) relationships are used. 3.2.3.2 Procedures for Information Modelling The first step for information modelling and rules of data normalisation were described below: 3.2.3.2.1 Steps for Information Modelling Step 1. The universe of discourse (UDO) or the part if real world should be selected properly with minimum redundancy but completely in terms of entities. Step 2. Entities are to be classified according to their attribute contents and merged, which have one-to-one (1:1) relationship into composite entities. Step 3. Their relationship among entities should be defined and named. Step 4. Normalization should done to reduce redundancy and increase integrity. 3.2.3.2.1 Rules of Data Normalization  Eliminating Repeating Groups: Make a separate table for each set of related attributes and give each table a primary key.  Eliminating Redundant Data: If attribute depends on only part of a multi valued key, remove it to a separate table.  Eliminate Columns not Dependent on Key: If attributes do not contribute to a description of the key, remove them to a separate table.  Isolate Independent Multiple Relationship: No table may contain two or more 1:N or N:M relationships that are not directly related.  Isolate Semantically Related Multiple Relationship: There may be practical constrains on information that justify separating logically related many-to-many relationships 3.3 Data modelling For an information system to be useful, reliable, adaptable and economic, it must be based on first on sound data modelling and only secondarily on process analysis. 3.3.3 Concept of Data Modelling A data model is a model describing the data in an organization. It provides a framework for abstracting the essential qualities or characteristics of data. Data modelling is the process of abstraction and documentation using a data model. Data modelling creates hierarchies of abstraction along two dimension: aggression and generalization. Aggression identifies data items as arts of higher-level, more aggregate descriptor. Generalization creates categories into which a data item may be classified. There are two major classes of data models - logical data models and physical data models. These two classes reflects the fact that efficient physical storage and retrieval of data must be designed around the physical characteristics if storage media and devices, but users of data should be able to describe, think about and use data without being concentrated about its physical storage. 3.3.4 Types of Data Modelling The data modelling consists of three interrelated pieces of information, the data object, the attributes that describe the data object and the relationship that connect data objects to one another. A data object is a representation of almost any composite information that must be understood by software. Composite information means something that has a number of different properties or attributes. Six different types of data models are briefly describe below: 1. Entity-Relationship Model The entity-relationship (E-R) data model is based on a presentation of a real world that consists of a collection of basic objects, called entities and of relationships among these objects. An entity is a thing or object in the real world that is distinguishable from other objects. Entities are described in a database by a set of attributes. A relationship is an association among several entities. The set of all entities of the dame type and the set of all relationships of the same type are termed as entity set and the relationship set respectively. In addition to entities and relationships, the E-R model represents certain constraints is mapping cardinalities, which express the number of entities to which another entity can be associated via a relationship set. The entity-relationship model is widely used in database design. 2. Relational Model The relational model uses a collection of tables to represent both data and the relationships among those data. Each table has multiple columns and each column has a unique name. The relational model is a record-based model. Record-based models are so named because the database is structured in fixed format records of several types. Each table contains records of a particular type. Each record type defines a fixed number of fields or attributes. The columns of the table correspond to the attributes of the record type. The relational data model is the most widely used data model and a vast majority of current database are based on the relational model. The relational model is at a lower level of abstraction than the E-R model. Database designs are often carried out in the E-R model and then translated to the relational model. In this project, relational model is used 3. Object-Oriented Data Model The object oriented data model is another data model that has seen increasing attention. The object-oriented model can be seen an extending the E-R model with notions of encapsulation, methods (functions) and object identity. Loosely speaking, an object corresponding to an entity in E-R model. The object-oriented paradigm is based on encapsulation of data and code related to an object into a single unit, whose contents are not visible to the outside world. 4.Object-Relational Data Model The object-relational data model combines features of the object oriented data model and relational data model. 5.Hierarchical Data Model The hierarchical data model represents a form of tree structure. No record can have more than one parent record but a parent record have any number of child records. A hierarchical database is s collection of disjoint trees with record occurrences nodes. 6.Network Data Model In network records and links as in the hierarchical model represents data but this represents a more generalized structure. A given record occurrence can have any number of immediate parents as well as any number of immediate dependants. Thus a many-to-many correspondence can be modelled more directly. 3.4 Application of Database Management System Database management systems are widely used in the real world. Here are some representative applications: • Banking: For customer information, accounts, loans and banking transaction. • Airlines: For reservation and schedules information. Airlines were among the first to use database in a geographically distributed manner-terminals situated around the world accessed the central database system through phone lines and other data network. • Universities: For student information, course registration and grades. • Credit card transactions: For purchases on credit cards and generation of monthly statements. • Telecommunications: For keeping records of calls made, generating monthly bills, maintaining balances on prepaid calling networks. • Finance: For storing information about holdings, sales and purchases of financial instruments such as stocks and bonds. • Sales: For customer, product and purchase information. • Manufacturing: For management of supply chain and for tracking production of items in factories, inventories of items in warehouse/stores and orders for items. • Human resources: For information about employees, salaries. payroll taxes and benefits and for generation of paycheques.

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