Report Example on Data Mining as a Business Tool

Introduction

Data mining refers to a technique of recognizing trends, patterns and correlations by analyzing significant volumes of data placed in repositories such as storages devices or databases (Ismail et al., 2015). It uses methods such as database systems, statistics and machine learning to recognize patterns of enormous data.

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Thus it is an essential tool that aids people to make wise business decisions, and it is a critical tool for business intelligence. It enables its users to analyze large volumes of data and reveal the hidden relationship in data that would otherwise not be recognized (Ismail et al., 2015). Another thing that makes data mining an important too is the way it optimizes the marketing campaigns. It aids businesses to comprehend which marketing campaigns are likely to create higher engagement, display individualized advertisement, optimize marketing and classify customers well (Ismail et al., 2015).

Types of Information Produced By Data Mining

Data mining can produce different kinds of information such as occurrences or associations which are connected to one event (Dringus, 2005). The linked information includes product clustering, store layout, catalogue design and shopping basket data. Another type of information produced by data mining is the events and sequences which are adjoined overtime. It involves classification, analyzing trends, relations and marching patterns to predict events. Characterization is another type of data produced by data mining (Dringus, 2005).

Characterization is the summarization of items’ available features in the focused division and creates the characteristic rule. The data which is suitable to consumer prescribed class is recovered by questioning the database and passed through summarization module to mine the significance of data in different abstraction levels. Lastly, data mining produces patterns, classifications which explain the group to which a product belongs (Dringus, 2005). It is found by analyzing the existing products which have been grouped and by following set of rules.

Company to Use Data Mining

When the company is searching for markets or marketing approaches, I will advise the company to use data mining. This will enable the company to learn changes, levels of customer satisfaction, and habits thus can make forecasts in marketing. Besides, when the company needs new services and products, data mining will be helpful. By using it, the organization will be able to make sales forecasts to identify which type of products and services it has to produce to the customers at a particular time.

Lastly, I will direct the organization to use data mining when trying to analyze unanticipated issues with sales, which are difficult to identify its causes. When the company faces a challenge in identifying the unexpected problems caused by sales such as customer mistakes, employee mistakes, or supplier mistakes, it will be helpful to use data mining to make such detections.

Conclusion

Data mining uses database systems, statistics, and machine learning to recognize patterns of enormous data. Thus it is an essential tool that aids people make wise business decisions, and it is a critical tool for business intelligence. It produces different information, such as associations, events and sequences, characterization, and patterns. It is essential to look for new markets or marketing approaches or analyze unanticipated issues and look for new services and products.

References

Dringus, L. P., & Ellis, T. (2005). Using data mining as a strategy for assessing asynchronous discussion forums. Computers & Education, 45(1), 141-160. https://www.sciencedirect.com/science/article/pii/S0360131504000788

Ismail, M., Ibrahim, M. M., Sanusi, Z. M., & Nat, M. (2015). Data mining in electronic commerce: benefits and challenges. International Journal of Communications, Network and System Sciences, 8(12), 501. https://www.scirp.org/html/4-9702035_62254.htm.