Assignment on Data mining- Good? Bad? Ugly?
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Assignment on Data mining- Good? Bad? Ugly?
The article’s main focus will be to align the use of data mining in building an effective business outcome. This is because managers may take advantage of it to convert data to dollars, which is a critical business of mining data. Data becomes an integral component of a business. Businesses are assisted in becoming efficient in decision-making through the information they collect and analyze. Data mining is about discovering and analyzing patterns, correlations, and trends surrounding large data amounts stored in repositories. The repositories may comprise storage and database devices. It becomes an important part of natural language processing, artificial intelligence, and machine learning. To achieve the best results in the business sector, it becomes crucial to look at the position and use of data mining, focus on operational gaps, and develop recommendations to improve operations.
Problem Statement
Understanding mechanisms and procedures for data mining requires a meticulous analysis, which is based on research developments. Broad steps have to be undertaken in enabling businesses to sail through their data mining processes smoothly. The above factor comes from the fact that many businesses are missing out on the right procedures and mechanisms to be undertaken to meet the needs of their businesses. Business personnel has been collecting irrelevant data from different sources (Ram, Zhang, & Koronios, 2016). In turn, they find the data useless because it is not as per the study’s principles and objectives. With this, such businesses tend to have a high possibility of increased costs and expenses in collecting, analyzing, and disseminating information for their use (Balco, Drahošová, & Kubičko, 2018). Such businesses also depend on consultants to undertake their work of collecting and analyzing information. The outcome includes exposing the data belonging to the business to third parties, which affects privacy and its associated security.
Purpose of the Study
The study’s purpose will revolve around creating clarity when it comes to ensuring that stakeholders in the business environments can appreciate the position and role of data mining in influencing business development (PBS News Hour, 2018). Businesses should be free to choose advanced technology in promoting effective decision-making outcomes. For this, data mining should be specialized and customized to ensure that it meets the objectives of the businesses it handles. The study reflects the different risks and challenges experienced by businesses, mostly the small and middle-businesses (Ram, Zhang, & Koronios, 2016). The focus is to identify how businesses can improve their position in the market. It evaluates the implications of using data mining compared to using other data collection methods, organization, and analysis through examples.
Literature and Analysis of Data
The paper’s main focus will be to ensure that readers can understand the role of data mining in ensuring business improvements among organizations. Significant literature review techniques are instrumental in enabling individuals to understand this relationship. To begin with, the first focus will be on the steps undertaken by organizations in achieving an efficient data mining framework for improving their operations (Oussous, Benjelloun, Lahcen, & Belfkih, 2018). They need to focus on having a hypothesis and assumptions regarding how, where, and when to use data mining techniques. The same applies to identifying all data sources with relevance to the hypothesis (Sivaraman, Gharakheili, Fernandes, Clark, & Karliychuk, 2018). Data points that have been discerned from different data sources should be tested and validated to identify their gaps and detrimental implications on an organization’s development. Many studies undertaken have to be correlated to the current study to ensure that their statistical models can make sense. The study creates an opportunity for individuals to use data mining techniques in their environments to support business operations. It is a foundation for promoting the positive use of data for the improvement of business operations.
References
Balco, P., Drahošová, M., & Kubičko, P. (2018). Data analysis is the process of energetics resource optimization. Procedia computer science, 130, 597-602.
Oussous, A., Benjelloun, F., Lahcen, A., & Belfkih, S. (2018). Big Data technologies: A survey. Journal of King Saud University-Computer and Information Sciences, 30(4), 431-448.
PBS News Hour. (2018, June 22nd). What the Supreme Court’s cellphone location data ruling could mean for your digital privacy. PBS News Hour. Retrieved from https://www.pbs.org/newshour/show/what-the-supreme-courts-cellphone-location-data-ruling-could-mean-for-your-digital-privacy
Ram, J., Zhang, C., & Koronios, A. (2016). The implications of big data analytics on business intelligence: A qualitative study in China. Procedia Computer Science, 87, 221-226.
Sivaraman, V., Gharakheili, H., Fernandes, C., Clark, N., & Karliychuk, T. (2018). Smart IoT devices in the home: Security and privacy implications. IEEE Technology and Society Magazine, 37(2), 71-79.