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Executive Summary for Relational Database Concepts

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INTRODUCTION Data management is one of the grey areas that every organization endeavors to improve almost daily. Most important is the data cleaning and data transformation processes. In actual sense, relational database offers a solution to this menace. Data organization, keeping, storage, and retrieval among other essentials can easily be realized by adopting relational data management model. In this kind of model, tables are made use of in such a way that data items are formally described and organized according to their level of relations. The data item contained in a given table represents a relation. I am convinced beyond reasonable doubt that through the use of relational database model, an organization can be able to effectively manage their wide range of information encountered on a daily basis. Relational database model offers a more efficient means of managing data. Some of the huge benefits are discussed as follows. WHY RELATIONAL DATABASE MODEL? This model is very unique and provides very sufficient means of data management. Its benefits are manifested in diverse ways which among others are its ability to enable you to store, manage, and retrieve your data in a flexible manner while maintaining vital data veracity. This is just but a tip of the ice berg (R. Snow, 2008). Accessing and transforming data Nowadays, the relational database models available are so powerful that they allow you an access to a query that easily transforms and retrieve data. This is actually a big solution to the challenges usually encountered in the data analysis processes. Such queries even have the capacity to allow you back-track on changes that may have been made on our data (Beynon, 2009). This therefore saves you the burden of having to keep several versions of data files involving such changes.

Data integrity Why keep huge numbers of flat files when relational database management can effectively do this for you? Data integrity is actually absolute in relational database. To enhance tidying, a unit data has to be divided into multiple sets which can easily be recombined and transformed. Data manipulation in this case involves sophisticated processes that may lead to loss of important information in the process. Relational database model however gives a solution to these bottle-necks (Ullman, 2011). Data cleaning Relational database model enables you to have a choice on the form of table, the data type, and the range of values to be accommodated in each column in a way that makes it possible to validate data upon entry into the system. For example, during data entry a command can be given that specify which type of information to allow in the system. Through this, the system will automatically reject any information that is not in line with the defined criteria. This instant feedback can help you notice and diagnose inconsistencies in your data. This provides an easier way of ensuring that your data free of errors. Data backup and restore Is it the worry of being able to retrieve lost data? Do not worry. Relational database makes it possible to recover lost data that may occur due to software errors or just human error in data manipulation. This is made possible by conducting backup operation occasionally. Restore action can be performed to get back the data (Kroenke, 2007). CONCLUSION Owing to the various facts noted about relational database model, it is worth mentioning that it is the way to go in order to cope with large amounts of data of the organization by embracing this kind of data management practice, the organization will be able to overcome the challenges encountered in the data handling processes.

References

Beynon, D. P. (2009). Database Systems 4th Edition. Basingstoke: Palgrave. Kroenke, D. M. (2007). Database Concepts 3rd Edition. New York: Prentice. R. Snow, D. C. (2008). Introduction to DB2. Database Management. Ullman, J. (2011). First Course in Database System. New York: Prentice-Hall Inc.

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