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Databases are commonly used through the computer industry and it is a collection of information which is organized so that it can be easily to be accessed, updated and managed data files. It can also be centralizing data and controlling redundant data. To verify the perfect solution, various types of Database Management System (DBMS) are available to fill the needs of the business problem that needs to be addressed. There are two major types of Database Management System will be mentioned in this paper such as Object Oriented Database Management Systems (OODBMSs) and Relational Database Management Systems (RDBMSs). Moreover, Data-mining technologies have the future of becoming the next most popular field area in database development. There are various types of data mining technology used in the process of accessing information from raw data. Each of these types of technologies are used for a category of reasons such as marketing, security and general information collecting. Mainly, the Data mining technology is used to test data samples instead of swathing the whole content of data and accepting analysts to verify and formalize patterns within the group or blocks of information.
Relational Database Management Systems
A relational database is a group of data which can be accessed easily from a set a table. A database stores data in relations, which is the user, receives as tables. Each relation is contained a tables, records, and fields. The relational models have different types of relationships as one-to-one, one-to-many, and many-to-many. A table contain products information of the orders, showing types of product, customers name or customer ID, product sale date, and the product prices with the columns. For example, the CLIENTS and AGENTS tables are related via an AGENT ID field; a specific client is associated with an agent through a matching AGENT ID.
Agent first Name
Date of hire
Agent phone number
Client First Name
Client Last Name
Relational databases are good for controlling huge amounts of data structured, alphanumerical data. For instance, Business Company use them to manage the records of transactions or personnel files. As their only data structure is tables, relational databases are incapable. And also they only work simple data types with limited, such as integers and would have trouble in user-defined data types and handling complex including multimedia. A relational database is created using the relational model. The application run in a relational database is known as a relational database management system (RDBMS). A relational database is the mostly range in data storing, over other models like the network model or the hierarchical database model.
Object oriented databases are also known as Object-oriented Database Management Systems (ODBMS). An object-oriented database management system (OODBMS) is indicated as objects used in object-oriented programming. Relational databases are different from object database. It is a database management system (DBMS) that supports the representing and invention of data as objects. This includes consist of support for classes of objects and the inheritance of class properties and methods by subclasses and their objects. Objects are used in object oriented languages like C++, Java, and others. Objects are generally contain of attributes and methods. Attributes are property of a relationship type or entity type. Attributes domain is set of allowable value for one or more attributes. Moreover there are five different types of attributes which are named as simple attribute, composite attribute, single-valued attribute, multi-valued attribute and derived attribute. Furthermore, methods are the behaviour of an object and functions.
The whole entire data can be stored in Object-oriented database and thus can process faster than relational databases, which are modify the data sets into storage parts enclosed the tables and then import data sets together again in reply to a queries. Moreover Object-oriented databases can also automatically catch the data in the client application's memory, by withdrawing additional calls to the DBMS's back and speeding up the reaction. The uses of CAD/CAM (computer-aided design and manufacturing) applications are approved in object-oriented database, which show composite data relationships. CAD/CAM applications are virtually works with object oriented databases and also use multimedia data types. In the meantime, object oriented databases are being used for healthcare checking systems in hospital because they are helpful for medical organization to work with than relational databases.
In addition, there are some companies in London like J.P. Morgan and Citibank are using object-oriented database management system (ODBMS) technologies in representing financial instruments like bonds and derivatives. The companies are modelling by using object-oriented analysis and design because object orientation helps virtually capture the structure of instruments, behaviour and support companies can get these products to a faster market.
As object-oriented model are being used for both the programming language and OODBMS, the programmers can manage the consistency easily between the two environments. The outcome for ODMBSs is not much code to create, decrease the time for development and shorten maintenance costs. Object-oriented databases are good for use with applications that must handle complex relationships within data objects. For instance, with the ODBMS, the company are modelling a Boeing 747, the relationships between aircraft parts are directly managed by the database. If you manage with a relational database, the company have to break down the aircraft into tables and then join the tables when they need to modify the aircraft (2012, Leavitt Communications). Since object-oriented database are performing well for using applications, can retrieve or store multiple data more expeditiously than RDBMS and the data structure changes are also more easily than RDBMS, therefore object-oriented database are getting growth compare to relational databases.
Advantages of the Database Approach
The advantages of the database approach is the data is control in a way that changes to the database structure and it's does not affect any of the programs that used to access the data. And it can also be the consistency of the data like Each item of data is control only one time so there is no riskiness of item being modified on one system and not on the another one. Furthermore, can database system can control the data redundancy. For instance, The same information may be centralize on several files in a non-database system. This ruins space and makes modifying more time consuming. This database system can minimises all these effects. As its provided the Database Management System (DBMS), users are able to specify constraints on data such as changing important files or essential feature or using a validation procedure to integrity of data. Moreover, controlling the entering the data system like someone who has access to logging into a restricted area and can only access user to a wide range of data that was previously control in different departments by the Database Administrator. The Database Management System (DBMS) determine an easy to use query language that allows users to get quick reply from their queries instead of requesting to a programmer to write queries for the entire department.
Data Mining versus Data Warehousing
The system designs, methodology used, and the purpose are the main differences of data mining and data warehousing. To identity trends with a set of data, data mining is use for the pattern. On the other hand, data warehousing is the process of storing and removing data to authorize simple reporting. Data warehouse is a relational database management system (RDBMS) (Jonathan, 2009, p.24). Data warehousing is the phenomenon which take place of data mining. Therefore, data warehouses arrange and compose the data into one main database and data mining remove from that database. Most of the performance and works are same in data mining and data warehousing. Data mining and data warehouses raise each other. The best known designed data warehouses can handle the data enrichment, cleaning, selection and changing steps which are also same reaction with data mining.