How Businesses Use DBMS Model - Example

How businesses use DBMS Model Name Institution Introduction Data management System (DBMS) is a software system that uses standard methods of storing, retrieving and runs queries on such data (Healey, 2010). It manages, organizes as well as providing means of modifying or extracting data by different users or other computer programs. Such software system is vital for handling of accounting information thus most businesses are currently using the software to manage their financial data. Examples of DBMS include, PostgreSQL, Microsoft Access, MySQL, SQL Server, Oracle, FoxPro, dBase and RDBMS. for the businesses to use these various DBMS effectively, the software come with a driver known as Open Database(ODDBC) that allows it to integrate with the other databases(OpenLink, 2013). However, the DBMS products can either be based on relational data model or logical data model though it has been a subject of constant technological changes. This report therefore, discusses the two models of DBMS by critically looking at their strengths and weaknesses to find out the best model for managing financial data. How businesses use DBMS DBMS introduction into organizations and business worlds was considerately vital for future growth since it offered businesses with an efficient, simple and reliable method of storing data, managing it and easy access (Healey, 2010). Businesses ought to have organized and efficient way of storing data as well as accessing them without problems or delays. DBMS in general has query ability, replication and backup, rule enforcement, security, computation, automated options and access logging. All these advantages encourage companies to adopt such system setups. DBMS is vital for the existence of businesses and provides the only means by which organizations can stay in the businesses. However, a good Database Management System must also co-exist with proper business plan and the companies must expect their profits in the long run but not immediately. Financial institutions heavily rely on DBMS for recording transactions, credit information and customer information. The ability of this system to handle accurately helps bank customers to access their accounts in any branch of the bank. This implies that non-reliable system would mean slower revenue and growth hence a company may risk losing its profits and market share. Which popular DBMS products are based in relational data model? DBMS that use relational data model stores data in tabular forms and the relationship among parameters or data is also stored in form of tables (Richard &Yan, 2013). In this context, the system groups data into various relations. Relational data model provides a direct method to specify data as well as queries where users state directly the information contained in the data base and the type of information that need for it. Eventually, users let DBMS to describe data structures so as to store information and it also shows retrieval procedures needed to answer queries. An example DBMS that uses relational data model is SQL that defines data by using a query language. SQL uses tables that correspond to the predicate variables. The other DBMS that use relational models include DB2, Oracle, Informix, MySQL, PostgreSQL and Sybase (Richard &Yan, 2013). DBMS based on relational data model works Some relation variables may include customer information, order, order line, invoice, invoice line and product line (Richard &Yan, 2013). When looking at customer relations, the system may classify basic information such as Tax ID, name, Address, city, zip, email and phone. It is therefore possible to classify the above customer relation information in a tabular form as the below shows. Name zip address Email Customer ID Tax ID City phone Which DBMS products are based on a logical model? Logical data models represent the data of the organization and organizing them in relation to relationships and entities (Mullins, 2011). The model is also independent of specific technologies of managing data. On the other hand, the model an abstract structure of information domain. Precisely, the logical model describes requirements of data from the business perspective or point of view. For instance, the banks DBMS allows the manager to view all fields and tables and uses logics to explain the variables that exist in the data or information The characteristics of the DBMS that are based on the logical model include (Milstein & Chapel, 2013): They describe data requirements for single projects or major subject areas It is possible to integrate them with other data models through shared entities They contain 100-1000 entities, though they are variable depending on data model scope They contain relationships among entities that cardinality and optional relationships The DBMS that are based on logical models include SQL/DS, DB2 and IMS and SQL oracles Strengths of relational models of DBMS The evident strength of this model is the fact that it is based on mathematical concept of relations (Teach-ICTM, 2013). It is therefore easy to compare relationships that exist between two or more values since the relationship is presented in a tabular form. Secondly, the model uses the mathematical concept of abstraction in defining and processing certain data. On the other hand, this model makes it possible to develop results using mathematical theorems and proof methods where the results apply to various applications. Moreover, the model allows users to use expressive as well as exact notation of mathematics. In this case, it allows accounts to use accounting formulas to process data and interpret it into a comprehensive manner. Furthermore, the model has tool that makes it possible to improve the design thus the system can easily adopt current technological advances or innovations (Teach-ICTM, 2013). The most outstanding feature of the model is that it is simple and easy to use thus it is useful in handling huge financial information. In addition, the data operations of this model are easy and simple to express while using few commands. Finally, the operations never require users to have a prior knowledge of the storage structures that are used. Weaknesses of relational model of DBMS The first limitation of this model is data complexity since it exists in several tables which link to each other via shared input values (Teach-ICTM, 2013). The relational DBMS does not compel designers to enforce a coherent structure of the tables thus allowing inexperienced programmers to design systems of unnecessary complexity. Poor design may limit future developments due to a poor choice of data types. On the other hand, the system can have the disadvantage of broken keys and records (Teach-ICTM, 2013). This model requires shared keys so as to link information across various tables. When key that link data types become different, the database may not link records without rework of report developer (Richard & Yan, 2013). Likewise, a table without unique key results in inaccurate results within the data base. Furthermore, the system requires developer expertise due to the complexity of the data types. For instance, critical database may require skills beyond small business performance. The problem exists when the system data base has been developed by different people. Finally, the model has limitations in relation to hardware performance since its complex queries machines with high processing power. Complex data and processes require computers with high processor abilities. Strengths and weaknesses of using logical model of DBMS The major advantage of this model is that it is easy to use and understand since people may identify where the information goes in the database. This is due to the fact that the model clearly lists all entities, attributes and relationships. Secondly, the model enables data managers to easily visualize business activities by indicating the type of information that relates to business like ID, name and address (OpenLink, 2013). Most importantly, the model is easy to construct since it lays out all the information and that it transfers information into diagrammatic form using few words. However, the model is difficult to modify (OpenLink, 2013). The logical data becomes hard to change since one editing one data set may affect all information since other relative information may be linked to them. Therefore, the user has to modify every single data so as to ensure that the new LDM is up dated and correct. Moreover, it becomes difficult to identify errors under this model. For instance if the model is designed for large databases, problems like insertion of wrong attributes using wrong data set may occur forcing the user to restart the whole process. The other limitation includes absence of finer details resulting in inappropriate description of the attributes. Finally the model is time consuming with regard to large data base and creating LDM for each attribute becomes difficult.   Conclusion In summary, the development of DBMS was a milestone in managing business data especially the financial corporations that deals with accounting. However, there are various models that explain how businesses use DBMS but this REPORT has chosen the two models: relational and logical models of DBMS. Some of the DBMS that use relational model include DB2, Oracle, Informix, MySQL, PostgreSQL and Sybase while logical DBMS include SQL/DS, DB2 and IMS and SQLOracles. Though different business entities prefer specific data management systems, the two models have certain weaknesses and strengths. Relational model for instance, has the advantage of applying mathematical concepts though it faces the weakness of data complexity. On the other hand, logical model DBMS is easy to use due to its simplicity but it always hard to modify. References Healey R. G. (2010). Data management systems. Retrieved from www.wiley.com/legacy/wileychi/gis/Volume1/BB1v1_ch18.pdf Milstein, B. & Chapel, T. (2013). Developing a Logic Model or Theory of Change. Retrieved from http://ctb.ku.edu/en/table-of-contents/overview/models-for-community-health-and-development/logic-model-development/main Mullins, C. S. (November 19, 2011). An introduction of database design: from logical to physical. Data and Technology today. Retrieved from http://datatechnologytoday.wordpress.com/2011/11/19/an-introduction-to-database-design-from-logical-to-physical/ OpenLink, (2013). Open conceptual data Models. Retrieved from http://virtuoso.openlinksw.com/whitepapers/open%20conceptual%20data%20models.html Richard, D. C &Yan, S. (2013). The company you keep: The relational models and support expectations of key developer relationships, Career Development International, 18(4), 328 - 356 Teach-ICTM, (2013). Advantages and disadvantages of relational database. Teach-ICT.com. 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