Relational Model And Missing Information Essay

Questions:

1. What is the problem? What are the requirements needed in order to solve that problem?

2. Why do you need to solve that problem?

3. How is it to be solved?

Answers:

Summary

Relational databases are used in most of the business organizations as well as educational institutions to store, maintain and utilize dynamic data. Dr. E.F. Codd applied various mathematical theories to design efficient relational databases. These can be classified into several groups:

Analysing requirements: involves analysing the business and its activities, functionalities and identifying the business as a whole (Thakkar & Kosta, 2014)

Data modelling: it involves logical structuring of database using various graphical modelling tools such as Entity-Relationship diagram, Data-Flow diagram, UML tools etc

Normalizing: decompose the large tables into smaller relations to eliminate the chances of redundant and duplicate records

1. What is the problem? What are the requirements needed in order to solve that problem?

It is very important for any organization to have a properly designed Database Management System in order to facilitate easy and effective database transactions, data update or modifications as well as insertion of new data in the database. An efficient DBMS provides a smart and effective design which implements all of the above requirements. Without a proper database model design an organization is sure to meet a lot of problems and difficulties in their business functions.

  • Without properly modelling the database system for a particular organization, it becomes more and more complex and difficult to manage the increasing amount of data.
  • With growing complexity, it is often time-confusing or even impossible to retrieve a desired record or information from the large pool of data (Selamat, Nguyen & Haron, 2013).
  • Database that contains large variety of data belonging to several individual entities, are hard to customize, manipulate or access by the database end-users.
  • Security is a very important factor when it comes to storing organization’s confidential information. Only a proper design model can ensure the security of database contents.
  • Often, databases contain multiple copies of similar data (i.e. data redundancy) thus unnecessarily increasing the size of data. It also causes various data anomalies such insert, update and delete anomalies.
  • An organization has lots of employees. Hence, it needs to provide a multi-user environment for its database users because multiple employees may need to access same data at the exact same time concurrently (Zhou, 2014). Absence of concurrency control strategies is sure to violate or distort the data in the database.

The basic database requirements any organization needs to fulfil are described below.

  • It needs to keep a directory like structure for supporting a strongly-typed database schema that only allows storing structured information.
  • Database objects and entities have complex relationships. There should be a proper method to represent those relationships in a simple and comprehensible manner.
  • Data integrity should always be maintained so that availability of valid, reliable and up-to-date data is ensured (Lo & Hung, 2014).
  • A good database design requires removing all existing data redundancies and repetitions in order to avoid data anomalies.
  • Optimized method to re-organize and reassemble data in many possible ways. There should be multiple layers of data abstraction such as logical and physical level of database to implement data transparency.

2. Why do you need to solve that problem?

The significance of ‘Database Management Systems’ is very much evident for business industries and organizations because they require providing highly efficient mechanisms for organising, managing and handling multiple data. The above mentioned problems and issues regarding database need to be resolved in order to facilitate an efficient DBMS.

It is next to impossible to manually enter and retrieve a relevant record from the vast pool or chunk of data stored in the database (Kroenke & Auer, 2013). For instance, an organization keeps records about its employees, customers, manufacturers, products, services, payments, transactions and delivery and many more. All those data belonging to separate entities need to be structured and classified to suit the requirements of the company.

3. How is it to be solved?

A relational database refers to a collection of two or more tables or ‘relations’ in which each record is represented in a row and termed as ‘tuple’ and each attribute or characteristic is presented in columns or fields. It is a tool to logically design the schema to support data independence (Jakovljevi?‡, 2012).

Enforcing relational database constraints: By implementing relational model the accepted input values for a specific column or field can be restricted. Other integrity constraints such as domain integrity, entity and referential integrity constraints are required to be implemented. Following the basic relational database principles essentially removes most of the complicacies and complexities of database.

Learning and Recommendations

Using relational database, data can be represented in a highly distributed fashion. The logical model of relational database shows the data transparency to various levels of users. Proper use of ‘keys’ is essential for implementing a successful relational design. Primary key is set for each entity so that one can easily distinguish the records in a table. Using SQL separate tables are interlinked with JOIN operations by connecting the primary and foreign keys.

Relational modelling can be used to identify the relationships among entities, establish access regulations and support data consistency. Moreover, NULL values should be treated carefully depending on the context and meaning they represent (Hoffer, Ramesh & Topi, 2013).

Security controls are employed more easily using sequence, triggers and various relational constraints such as domain key, check and unique constraints, NOT NULL constraints, primary and foreign key constraints etc. The proper utilization of relational modelling tools removes any kind of data ambiguity that might exist in the database.

Conclusion

Relational database design is used to create the logical structure of the database. It gives potential benefit to the users of database by facilitating data independence and precision. Various data manipulation languages such SQL are used to store and extract data. The advantage of running query language over relations is the user does not need to know how the database works or what the physical structure (e.g. indexing, clustering etc) of the database is (Atay, 2014). Relational databases are essentially centralized and managed by the DBA. Additionally, it prevents the need of searching the whole database sequentially to retrieve a particular record. The purpose of applying relational design techniques is to maximize the database performance and efficiency.

Reference List

Atay, C. (2014). An Implementation of Bitemporal Relational Database Management Systems. Pamukkale J Eng Sci, 20(2), 54-62. doi:10.5505/pajes.2014.25743

Hoffer, J., Ramesh, V., & Topi, H. (2013). Modern database management. Boston: Pearson.

Jakovljevi?‡, S. (2012). Relational Model and Missing Information. JITA, 3(1). doi:10.7251/jit1201032j

Kroenke, D., & Auer, D. (2013). Database concepts. Boston: Pearson.

Lo, C., & Hung, H. (2014). Towards a UML Profile to Relational Database Modeling. Appl. Math. Inf. Sci., 8(2), 733-743. doi:10.12785/amis/080233

Selamat, A., Nguyen, N., & Haron, H. (2013). Intelligent information and database systems. Berlin: Springer.

Thakkar, A., & Kosta, Y. (2014). Improving Efficiency of Relational Classification Technique Based on Relational Database Using Contribution of Tables. International Journal Of Data Mining And Emerging Technologies, 4(1), 1. doi:10.5958/2249-3220.2014.00015.9

Tian, L., Zhu, Y., & Zhu, H. (2012). A Relational Data-based Lightweight Workflow Engine Model. IJEME, 2(4), 1-8. doi:10.5815/ijeme.2012.04.01

Yue, L. (2014). Relational Database Architecture Refine Based on the Storage Space Estimate. AMM, 536-537, 647-652. doi:10.4028/www.scientific.net/amm.536-537.647

Zhou, X. (2014). Research on XML Documents and Relational Database Mapping Based on XML Schema. AMM, 599-601, 1683-1687. doi:10.4028/www.scientific.net/amm.599-601.1683

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