DATA MINING

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This is the process by which companies change raw data into useful information. Business technology through the use of some software allows identification of some patterns in large batches of row data which enables them to learn more about their customers. The benefit of data mining is that it assists in providing effective marketing strategies. It is dependent on effective data collection and warehousing.

Businesses such as grocery stores and supermarkets are well known for data mining as a way of identifying customer tastes and preferences. Supermarkets provide supermarket cards that allow them to offer products at subsidised prices compared to non members. Information on the card can assist in analyzing customer preference and enable the organization to monitor the buying habits of the customer.

How does data mining benefit the business in?

Predictive analytics to understand the behaviour of the customer

A business is a risk in which the investor places a bet hoping that the outcome favours the business. Success depends on having the ability to predict the future hence having the ability to prepare for the outcome (Cerrito, 2011). Data mining provides relevant and substantial amount of data from customers analyzing their trends hence the enabling the ability to predict what they will purchase next. Having information about the future or a rough estimate provides a foot path which guides in decision making. An organization is able to prepare for future changes and develop alternatives to save it from compromising situations.

Association in discovery in products sold to customers.

Large companies which include Banks, brokerage institutions, insurance, and telecommunication benefit from data mining as they are able to acquire and analyze what customers prefer and want more. However, small businesses as well are able to analyze data and enable the business to identify what products customers prefer and how they prefer it. This benefits the company in decision making. Market segmentation is also enabled whereby the organization is able to divide the market based on what products the sections consume.

To discover business intelligence from web customers.

Online interviewing and questionnaires assist the company to gain knowledge about customers and their views about respective organizations. Through posting various advertisements or questions online enables the customer to share their views on the business. Data mining groups all this information and through checking out for various patterns or information the company is able to gain more knowledge hence the ability to make intelligent and effective decisions.

Clustering to find related customer information

Clustering is a technology that involves putting similar objects together. Members of a cluster are more similar to one another sharing the same characteristics. Data mining can be viewed as a way of clustering as one of its benefits is to put a batch of raw data and rearranging it according to a specific and definite pattern. Data mining and clustering are interdependent components that are significant to a business organization. Data mining assists in exploring data which is later clustered to provide relevant information to assist in decision making. Through data mining segmentation which is a result of clustering is enabled hence providing accurate and detailed information.

Information provided by data mining is accurate depending on the quality and the effectiveness of the search engine employed (Ebecken, 1998). Information gained through data mining is only valid if the organizations systems are monitored and assessed frequently. Data mining is an approach which should be only implemented when all its merits have been approved as well as its information reliability. It is difficult to come up with clear information about the future as anything can happen then. The mere fact of knowing the future changes it. It is only possible to determine the validity of data mining information by aligning its results to expected results. They may or may not be successful. A company should not fully depend on information derived from data mining as it may or may not be successful. Data mining is mainly affected by various factors that may render it ineffective such as; lack of data standards, timelessness of updates, and human error. These three factors make data mining less effective hence it requires a lot of attention while it is being used in making decisions.

Minimal privacy concerns have been raised due to data mining.

Private information leakage may lead to cases of fraud or harm to the individual whose information has leaked. Cases of fraud have risen especially when dealing with loans due to the leakage of personal information into the internet.

Customers lack of awareness that their personal information is being fed into the organization’s database; which leads to discomfort and insecurity among consumers. Consumers feel that their privacy is violated when they find out that their own personal information is being monitored.

Dilemma in which companies risk losing their competitive edge by allowing consumers to decide whether their information should be used in making business decisions or the other way round (Aggarwal, 2012). Most people would not privacy intrusion hence the company is at a risk of losing viable information gained through data mining. Data mining involves the use of much more detailed information which many clients are not willing to let get exposed.

To a great extent this concerns are valid and every individual under the constitution is entitled to privacy as a right. Data mining is essential for the organization but on the other hand privacy is a right that should not be violated by the company at the expense of the client. If the organization decides to employ data mining it should ensure security of the client’s information and create firewalls to prevent leakage of into the internet.

The company should involve the client while deciding to dig out their personal details for analysing and decision making. It should as well provide details as to why it chooses to use data mining as a way to acquire information for decision making. Because this information has been acknowledged to be highly sensitive companies have decided to proceed with prudence only limiting themselves on what is relevant and what is not. This measure is employed for the three measures.

Consultant firms mainly deal with data mining with companies such as Timberlake Consultants Ltd, Trilogy Consulting Corporation, and Pro-Metrics Consulting Services. All three companies have gained competitive advantage through having information about customers.

References

Aggarwal, C. C. (2012). Mining text data. New York: Springer.

Ebecken, N. F. (1998). Data mining. Boston: WIT Press/Computational Mechanics Publications..Cerrito, P. B. (2011). Data mining to determine risk in medical decisions. Amsterdam : IOS press.

Data Mining
Paper instructions:
Assignment 4: Data Mining
The development of complex algorithms that can mine mounds of data that have been collected from people and digital devices have led to the adoption of data mining by most businesses as a means of understanding their customers better than before. Data mining takes place in retailing and sales, banking, education, manufacturing and production, health care, insurance, broadcasting, marketing, customer services, and a number of other areas. The analytical information gathered by data-mining applications has given some businesses a competitive advantage, an ability to make informed decisions, and better ways to predict the behavior of customers. Write a two to three (2-3) page paper in which you:
1. Determine the benefits of data mining to the businesses when employing:
1. Predictive analytics to understand the behavior of customers
2. Associations discovery in products sold to customers
3. Web mining to discover business intelligence from Web customers
4. Clustering to find related customer information
2. Assess the reliability of the data mining algorithms. Decide if they can be trusted and predict the errors they are likely to produce.
3. Analyze privacy concerns raised by the collection of personal data for mining purposes.
1. Choose and describe three (3) concerns raised by consumers.
2. Decide if each of these concerns is valid and explain your decision for each.
3. Describe how each concern is being allayed.
4. Provide at least three (3) examples where businesses have used predictive analysis to gain a competitive advantage and evaluate the effectiveness of each business’s strategy.
5. Use at least three (3) quality resources in this assignment. Note: Wikipedia and similar Websites do not qualify as quality resources.