Data mining

Data mining in business

CRM- For maintaining an effective relation with the customer data and information is needed. By data mining technologies the information that is collected can be analyzed. It helps to remove the confusion of how to retain the consumer.  Fraud Detection- Data mining helps to turn the relevant data into information and it gives meaningful patterns. It helps to detect the fraud activities which in turn help the users to get protected information. This method is time savvy and simple.

It is important as it helps to identify the customer behavior toward the offerings of the firm. Business organizations are able to make more appropriate decisions. It therefore helps to improve the customers’ loyalty, making them more loyal towards the company. The obtained data is helpful in predicting which consumers are going to the competitors and which ones are staying with the company. The credible patterns which are important for the success of business can also be explored.

It supports the business and helps it in attaining a competitive advantage and to attain information. It helps the business to provide customer satisfaction which in return increases the profits for the firm. Companies which are having large datasets use data mining to analyze the data. The hidden and predictions which are not discovered can be explored helping in effective decision making.

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Data mining is an essential tool that is used by many of the industries nowadays. It is important as it helps to provide and identify the useful information from huge amount of datasets in all industries. Industry use data mining to get a rise in their revenues and o reduce the costs. It is a technique of identifying the patterns to develop effective strategies and make better decisions. It is seen that retailers are facing serious issues as the environment is uncertain and dynamic. Retailers are finding ways to seek effective market campaigns.

They are gathering huge and large amount of consumer data. It requires accepted procedures to convert the collected data into useful information. The useful information will help to make appropriate business decisions. Retail industry is adopting for a strategy through which they can target the potential customers who will help the business to grow and make it more profitable. Data mining will help the companies to have a focus on the most important information in their data warehouses.

It helps the business organizations to predict the behaviors and the ever changing trends which will make the organizations proactive. Data mining in retail sector is used for variety of purposes like to target the potential customers, to increase the revenues, market campaigns, etc. retail industry will have huge success and will sustain in this ever changing marketplace by the adoption of data mining technology.

Major security, privacy and ethical implications in data mining

There is a risk in data mining that the collected data can fall into the wrong hand because it is long process which includes; encryption, intrusion detection, access control, auditing and backup of the data causing security and privacy issues. There is a need for the business to protect the personal information of the customer otherwise it may cause security, privacy and ethical issues.

On the other hand, the loss of the employee’s privacy in internal business such as the browsing history of the every employee can reveal personal data that may cause reputation and financial loss. At the same time, if the law enforcement agencies collect the information in the data mining then the person in this process can be treated as a possible criminal (Gorunescu, 2011).

The security and privacy implications also increase the overall cost the business that also affects the product and service cost. The big data is useful to improve the quality of the data, but in the concern of the data mining, it reduces the overall quality of the original data, it is only useful for the show-off.

The data mining provides the data in a table format that is also be useful for the fraud person, he can directly use this data in the ascending and descending order. On the other hand, the big data can be used by the fraud person in the form of pick out one from all data. The ethical issues may be generated in the data mining; it is because the data are stored in the computer by an organization. The company may misuse the details of the customer like email, mobile number, name and account detail by sold out the detail to another company (Han et al., 2011).

In the healthcare industry, the data mining requires the patient information such as confidential disease of the patient, contact number, address that the person do not want to share with another. But all these information are used by the research company for the future solution of the problem of specific disease. In the concern of the ethical solution of the data mining, it is necessary to maintain the transparency and the accountability that can hand out to a privacy branch for the security.

Implications for the business sector

The data mining can provide the help to the business by handle the collected data in the secured hand and it is their responsibility to security. At the same time, the security of the data will provide competitive strength to the business and the competitor will not able to find our business data of market research (Kantardzic, 2011). The collected information by the law enforcement agencies in data mining process make available a high secured data.

The data mining provides short and deep details of the big data with the high security, so there is no need to spend more time for the access the data. The security of the big data is hard and costly but the data mining reduces the store keeping and handling charges. In addition, the data mining controls on the access of data by the reduction in the size of available data. For example- The Wal-Mart used the data mining in their point of sale of the daily basis transaction, according to the current scenario.

By the use of this data mining technique and analysis, the organization would be able to understand the marketing for the development, predict the customer need and determine the sales trends. The information is stored in the database which is centralized by the organization. In addition, the Wal-Mart uses their data mining by the data mining software and it categorized their items for the browsing the data easily.

The protection of the personal information can be done by the data mining by the use of backup, auditing of the collected data and this security also help to promote the privacy (Larose, 2014). The transparency in the data mining provides a high security that helps to face the privacy challenge in the business market. The data mining provides a simple structure of the big data that is very helpful to show off the data in the presentation and other growth representation.

By the use of this potential growth chart a company can arrange appropriate production and the buying behavior of the consumer also known. For example- Tesco is also a good example that uses the data mining in their business to take an intelligent action.

Tesco gathers the data about customer to drive in the market and data mining is done for the critical analysis of the retail product. To survive in the market, Tesco provides the offers and coupons to the customer according to the customer looking contents in the company baskets and all the details of the customer are collected by the data mining (Linoff & Berry, 2011). This is also a technique of the promotion of the product where the company also provides coupons for public on the most recent contents. It provides the accurate prediction to the business and the target can fulfill by the production team of Tesco

The businessman also has details of their employees and regular customer and may use this information for the social security such with their birthday, introduce about festival offers and provide their accessed product. It also reduced the information that is not relevant for the business and affects the ethics of the employees and customer. At the same time, data mining in the operation and manufacturing can easily determine the control parameter to increate he production.

The data mining also helps to the government to understand the financial transaction and analysis the records of the relative organizations (Witten et al, 2016). It helps to the business to understand the purchase behavior of their customer by the use of different ways. For example- A credit card company uses data mining for distribute new credit products to the trusted and regular customer and identify them. For this company can take a small test of the customer for the purpose of quality testing to timely deposited customer, their recent transaction indicates their quality of timely deposited transactions.


Enggjournals.(2013) [Online] Retrieved from:

Gorunescu, F. (2011). Data Mining: Concepts, models and techniques (Vol. 12). UK: Springer Science & Business Media.

Han, J., Pei, J., & Kamber, M. (2011). Data mining: concepts and techniques. Netherlands: Elsevier.

Kantardzic, M. (2011). Data mining: concepts, models, methods, and algorithms. UK: John Wiley & Sons.

Larose, D. T. (2014). Discovering knowledge in data: an introduction to data mining. UK: John Wiley & Sons.

Linoff, G. S., & Berry, M. J. (2011). Data mining techniques: for marketing, sales, and customer relationship management. UK: John Wiley & Sons.

Ngai, E. W. T., Hu, Y., Wong, Y. H., Chen, Y., & Sun, X. (2011). The application of data mining techniques in financial fraud detection: A classification framework and an academic review of literature. Decision Support Systems, 50(3), 559-569.

Witten, I. H., Frank, E., Hall, M. A., & Pal, C. J. (2016). Data Mining: Practical machine learning tools and techniques. USA: Morgan Kaufmann.

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