ITM535 MOD4 Discussion / Evaluation of Data Mining

Discussion/Evaluation of Data Mining
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Discussion / Evaluation of Data Mining
Data mining is the practice of sorting through large data using computing processes to determine the existence of recurring patterns and relationships towards solving issues through data analysis. In the analysis of large data sets, data mining relies on the construction of suitable data models and structures employed in processing, identifying and building the required information (Gandomi & Haider, 2015). The process involves running of complex queries on the stored data to determine patterns and relationships that can be capitalized on in solving particular problems. The commonly employed technique in the mining of large data is the use of associations. Simple correlations are made between various items of the same type to determine patterns. Repetitive patterns aid in predicting future behaviors and thus, narrowing the data scope (Gandomi & Haider, 2015). The other means through which data mining can assist in extensive data analysis is by classification. Multiple attributes found in a given data set can be identified in a particular class, like classifying consumers based on age and preferences among others. Data sets can also be examined based on one or more characteristics and grouped to give a structured opinion. The technique is useful since tests can be undertaken to confirm and justify the particular view. Based on the explained approaches and others, data mining simplifies the analysis of large data sets, hence aiding in decision-making.
In business intelligence, data mining enables the detection of deviations from the expected patterns, hence detecting fraudulent activities. By comparing current events as recorded with old behavior profiles, frauds are exposed, thereby creating an intelligent business environment (Kabakchieva, 2010). Since data mining can provide meaningful data patterns, it turns data into information, which is considered as useful knowledge. By protecting the information available within a given data set for all users, data mining contributes to business intelligence (Kabakchieva, 2010).
References
Gandomi, A., & Haider, M. (2015). Beyond the hype: Big data concepts,...