Sample about Data Mining

Data mining is the process of sorting large amounts of data with an aim of picking out the information which is relevant. As much as it finds its large use by financial analysts as well as business intelligence organizations, it is also widely used in the sciences in extracting relevant information from data sets that are enormous and generated by modern observation as well as experimental methods. Data mining is sometimes called data knowledge discovery or data.It is a powerful and new technology that has been adapted by companies to help them in focusing on the most crucial information in their data bases or data warehouse (D. Hand, H. Mannila, P.

Smyth 2001). Data mining involve data mining tools that help in predicting future trends as well as behaviors, enabling businesses to make decisions that are knowledge-driven. It is also supported by some technologies that enable it to be easily applied in the business community. These technologies include massive data collection, data mining algorithms and powerful multiprocessor computers.

Definition of terms. There are several terms that are related to Data mining. One of these terms is Data Cleansing which is defined as the process through which consistence ad correct recording of all the values contained in a data set is ensured. Another term is data navigation which is the process through which different dimensions, levels and slices of details that belong to a multidimensional database are viewed.

Another term is data warehouse which is defined as a system through which massive quantities of data is stored and delivered.Data Visualization is the interpretation in multidimensional data of complex relationships visually whereas a decision tree is a structure that is tree-shaped and used to represent a set of decisions. It is through these decisions that rules for the data set classification are generated. Data mining has found quite a lot of usage in the modern world, especially in this wake of technology where companies are acquiring a lot of data as they strive to compete in the technological world (Galit Shmueli, Nitin R. Patel and Peter C.

Bruce 2006).By use of predictive techniques, data mining has been effective in uncovering patterns in data. These patterns reveal areas that are necessary for process empowerment. The patterns uncovered also help organizations in making better as well as timelier decisions. Data mining also enables organizations such as companies to increase fraud detection and improve risk management.

Data mining is also believed to help SPSS customers in solving problems relating to business. SPSS data mining services as well as solutions have enabled many organizations to obtain recommendable results in many areas (Kantardzic, Mehmed 2003).For instance, organizations through data mining have been able to double online profits through improving or boosting personalization features. They have also been able to improve the rate of response of direct mail campaigns by almost 100 percentages. Pros and Cons of Data Mining Data mining can help direct marketers through providing them with accurate and useful trends on the purchasing behavior of their customers. It can also assist or provide aid to financial institutions mostly in areas including loan information and credit reporting.

It can also help law enforcers in identification of criminal suspects an also apprehending them by examining location trends, habit, crime type and other behavior patterns. It can also assist researchers by spending up the process of data analysis. However, there are some drawbacks of data mining. Data mining may lead to violation of privacy law for example when personal information is enclosed without owners’ or customers’ consent (Pang-Ning Tan, Michael Steinbach and Vipin Kumar 2005).

Data mining may also fail to fulfill security issues. For instance, hacking of personal information may result to identity theft.In addition unethical people as well as businesses may use the information got from data mining to discriminate against particular group of people or take advantage of those people who are vulnerable. For the electronic mgf service company, data mining would work successfully. This would only be realized if privacy issues as well as security issues are highly observed.

On observing this, the customers will be assured of their security and their relationship with the organization will stabilize leading to improved profits and success of electronic mgf service company.This data mining concept would also work for this company if all the data mining tools and data mining techniques are well put in place and proficiently applied. Most companies have already used data mining and benefited from it. An example is Wal-Mart which uses data mining in a view of transforming its supplier relations. It allows more than 3500 suppliers to get an access to data on their products as well perform data analysis.

The suppliers use the data in identification of customers’ patterns of buying at the start.Another company is the National Basketball Association (NBA) which has used data mining application that is in conjunction with recording of images of basket ball games. In summary, data mining is a very crucial process that many companies and organizations should be encouraged to adopt. As discussed above, its advantages out do the disadvantages and therefore prosperity of any company that receives a lot of data in its data warehouse can only be achieved through application of data mining.