Data Mining and Decision-Making in Business-Samples for Students

Questions: 1.Briefly summarise why Data Mining is used in Business. 2.Identify the major security, privacy and ethical implications in Data Mining. Answers: 1.Data mining in business Importance of data mining Data mining is a process of accessing some confidential and hidden data with the help of software. Data mining helps organizations on taking crucial decisions. Data mining is needed for retrieving information from the piles of database, which will be used for analytical purpose. This process is undertaken by leading corporate houses to identify and gain profitability and competitive advantages (Tan, Steinbach Kumar, 2013). Data-mining in business Data mining can be a considerable help in business as it is used to discover various data, their types and relationship between various data accessed from a wide database. This helps in successful decision-making. It further benefits in developing effective marketing campaigns, which have a considerable impact on business (Shmueli Lichtendahl Jr, 2017). Benefits of using Data-mining 1) Data mining used to identify fraudulent transactions. 2) Data mining benefits in developing accurate risk models that in turn helps in successful decision-making. 3) Data mining helps in improving the quality and safety of the product by evaluating the customers feedback. 4) Data mining is undertaken for improving the conversions, which in turn increases the customer satisfaction. This is done by analyzing the past sales and customers feedback. 2.Introduction Data mining is a process of gathering, using and sharing information by accessing a huge set of databases. Data mining is becoming increasingly popular as it is undertaken by different organizations for effective decision-making. This is popular primarily because of the techniques used in application of data mining. Examples of such techniques discussed in this article are knowledge discovery, neural networks and case based reasoning. Data mining and Decision-making in business Gaining knowledge about the customers or the market helps the organization in strategic planning and effective decision- making. It is a process of gathering, analyzing and storing information on basic of the customers demands and capture market. This whole process is a result of data mining and hence it holds utmost importance in decision making in business. There are different techniques of data mining such as statistics, artificial intelligence and machine learning. Furthermore, there are many facets of data mining as well, the most important one being the web mining. Web mining considerably helps in building a proper and effective business strategy by reaching the target customers. Data mining also helps in depicting the market demand and customer behavior. Information about customers behavior helps in producing more innovative product and services customized according to the customers demand. Thus, data mining helps in effective decision making in business. Conclusion Therefore, it can be concluded that data mining is an integral part of todays business world as effectively helps in strategic planning and proper decision-making. Data mining makes use of the companys intellectual assets in establishing new objectives thereby improving the techniques used in business and increasing the profits of the organization as well. In this competitive world, data mining proves to be an important tool for gaining a competitive advantage in the market. Bibliography Tan, P. N., Steinbach, M., Kumar, V. (2013). Data mining cluster analysis: basic concepts and algorithms.Introduction to data mining. Shmueli, G., Lichtendahl Jr, K. C. (2017).Data Mining for Business Analytics: Concepts, Techniques, and Applications in R. John Wiley Sons. A Research Study: Using Data Mining in Knowledge Base Business Strategies. (2017).Scialert.net. Retrieved 8 August 2017, from https://scialert.net/fulltext/?doi=itj.2006.590.600 Rokach, L., Maimon, O. (2014).Data mining with decision trees: theory and applications. World scientific.