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Data Mining and Collection

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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.

1. Determine the benefits of data mining to the businesses when employing active analytics to understand the behavior of customers and associations discovery in products sold to customers.

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. Choose and describe three (3) concerns raised by consumers.

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' strategy.

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1. Determine the benefits of data mining to the businesses when employing active analytics to understand the behavior of customers and associations discovery in products sold to customers.

Data mining is taking a look at the inventory of information that you normally generate as part of your ongoing business, and peeling it apart for insight into your business (Lane, 2012).

Data mining is an aide to strategic, tactical and operational decision-making in situations where numerous variables, affecting costs or benefits, impinge on the eventual outcome of the course of action that a company might decide to take (Data-Mining-Guide, 2005).

Bal et. al (2011) said that data mining can be used in Direct Marketing, Customer Acquisition, Customer Retention, Cross-Selling, Trend Analysis, Fraud Detection, and Forecasting in Financial Markets.

According to Bal et. al (2011), these are the benefits of data mining:
- Data is at the heart of most companiesâ?? core business processes and data mining techniques can discover information that many traditional business analysis and statistical techniques fail to deliver.
- Data mining creates information that can be leveraged by the organization to create a competitive advantage.

Data mining brings benefits to the following industries (Data Mining Techniques, 2012):

Marketing / Retail
Data mining helps marketing companies to build models based on historical data to predict who will respond to new marketing campaigns, such as direct mail, online marketing campaigns, etc. Through this prediction, marketers can have an appropriate approach to sell profitable products to targeted customers with high satisfaction.

Data mining brings a lot of benefits to retail companies in the same way as marketing. Through market basket analysis, the store can have an appropriate production arrangement in the way that customers can buy frequent buying products together pleasantly. In addition, it also helps the retail company offer a certain discount for particular products that will attract customers.

Finance / Banking
Data mining gives financial institutions information about loan information and credit reporting. By building a model from previous customerâ??s data with common characteristics, the bank and financial institution can estimate what the good and/or bad loans are and their risk level. In addition, data mining can help banks to detect fraudulent credit card transactions to help credit card ownerâ??s prevent their losses.

By applying data mining in operational engineering data, manufacturers can detect faulty equipments and determine optimal control parameters. For example, semi-conductor manufacturers had a challenge that even when the conditions of manufacturing environments at different wafer production plants are similar, the quality of wafers are not the same and for unknown reasons even contain defects. Data mining has been applied to determine the ranges of control parameters that lead to the production of the golden wafer. Then those optimal control parameters are used to manufacture wafers with the desired quality.

Data mining helps government agencies by digging and analyzing records of financial transactions to build patterns that can detect money laundering or criminal ...

Solution Summary

The solution describes the benefits and uses of data mining in managerial decision making.