Data Mining Process Database Design

Question: 1.What are some potential problems of poor database design? 2. Discuss some of the ways in which data mining can help a company generate more business. Answer: Potential Problems of Poor Database Design The major issue of the poor database design occurred during fetching the data because the related data is scattered on various tables. As opined by Coronel and Morris (2016), at the time of updating of the overall database, similar attributes are changed, and it is able to place the data redundancy, which must be avoided while designing the database. Additionally, the security issues are also taking place due to data inconsistency, which also occurs if the database is designed in a poor manner. Moreover, as commented by Hernandez, (2013), the database became unnecessarily complex due to the poor designing as well as the hidden information are also can be accessed in an easier way and that is not a good example of a standard database. It is necessary to mention that, due to poor design of a database, it became slow as well as inflexible for fetching the data using any programming language including structured query language (Tabernero et al. 2014). Ways of Data mining for generating more Business Data Mining is highly helpful in generating more business in various ways along with appropriate process (Refer to Appendix 1). Few ways are: Database Marketing: Database Marketing refers to gather the information of the appropriate needs of the organization. According to Shmueli, Patel and Bruce (2016), data mining allows to detecting the requirements according to the customers for designing the database of the organization. As a result, targeting the customers becomes easy. Sales Forecasting: Russell (2013) argued that data Mining is highly reliable in analyzing the sales forecasting along with the Planned Obsolescence strategy for determining the numbers of the customers who are actually involved with the organization. Customer Loyalty: Data Mining is able to generate more business along with customer loyalty by providing suitable ways to attract the customers towards the organization. Data Mining also does provide advertisement with "Employee Innovation tool to various websites in a cohesive manner (Provost Fawcett, 2013). References Coronel, C., Morris, S. (2016).Database systems: design, implementation, management. Cengage Learning. Hernandez, M. J. (2013).Database design for mere mortals: a hands-on guide to relational database design. Pearson Education. Provost, F., Fawcett, T. (2013).Data Science for Business: What you need to know about data mining and data-analytic thinking. " O'Reilly Media, Inc.". Russell, M. A. (2013).Mining the Social Web: Data Mining Facebook, Twitter, LinkedIn, Google+, GitHub, and More. " O'Reilly Media, Inc.". Shmueli, G., Patel, N. R., Bruce, P. C. (2016).Data Mining for Business Analytics: Concepts, Techniques, and Applications in XLMiner. John Wiley Sons. Tabernero, P., Fernndez, F. M., Green, M., Guerin, P. J., Newton, P. N. (2014). Mind the gaps-the epidemiology of poor-quality anti-malarials in the malarious world-analysis of the WorldWide Antimalarial Resistance Network database.Malaria journal,13(1), 1.