Data Mining aricle example

Data mining the next big thing in technology, if used properly it can give businesses the advance knowledge of when they are going to lose customers or make them happy. There are many benefits of data mining and it can be accomplished in different ways. The problem with data mining is that it is only as reliable as the data going in and the way it is handled. There are also privacy concerns with data mining. Keywords: data mining, benefits, privacy concernsData MiningBenefits of Data Mining for a BusinessData mining can be explained as the process of a business collecting data on their customers or potential customers to increase customer business.

A business will collect data on their customers or potential customers and use that data to give them coupons, promote sells, and analyze buying and selling trends. Data mining can benefit the customer as well as the business. Data mining can be used in the retail industry, the finance industry, and the healthcare industry. Any industry can benefit from data mining but those are the top three (Turban & Volonino, 2011).

Data mining is a way for large businesses to get to know their customers.The information gathered from data mining can let a large company learn what their customers want and how they want it. It can also benefit large companies get to know their employees, the company can learn how to satisfy their employees and then they might work better. Showing employees that a big company knows a little bit about them gives the impression that the company cares. When employees think that the company cares they tend to work better. With processes that have benefits, there are also some concerns.

Privacy is a concern of the customers involved. Also, customers are concerned with what is being done with the data that is collected and how the businesses are collecting the data. No one likes to feel like they are being spied on. Another concern can be the worth of the data.

The predictions are only as good as the data that it is presented with, as with other information systems, it is based on garbage in, garbage out.Predictive Analytics BenefitsPredictive analytics sorts through the data that is collected and analyze the data for patterns from the customers. Then it will make suggestions based on the data of what the customer might buy next or not be interested in buying (Turban & Volonino, 2011). After the analysis it can be used to understand the behavior of the customers.

There are many benefits that business can receive from predictive analytics. The following information can be beneficial to a business that comes from predictive analytics; the customers who respond to new products, and who respond to discounts, who buy specific product categories, which customers are most loyal, and which customers might not be using the business very much longer.This information is beneficial because, it can alert a business to when they might be losing a customer, and it gives the business the opportunity to reward the current and most loyal customer. It gives the business the opportunity to contact the customer that it might be losing and try to win the customer back or get the reason they are no longer using the business. It gives the business an idea of what products are more likely to sell when and they can plan accordingly. They can get more hot weather clothes in the warmer months because that’s when it has been predicted that customers buy hot weather the most and offer less cold weather clothes at the same time.

IT would prevent businesses having overstock of items because the items didn’t sell because the items were offered at the wrong time of year.Associations Discovery Association discovery can be defined as analyzing data into relationships while sorting through a massive amount of data. Association discovery finds products of services that are associated together by a transaction. For example, if a customer buys chicken noodle soup they may also buy tissues because chicken noodle soup goes with having a cold and so do tissues, and they may have been purchased together multiple times by customers in the past and a pattern was noted. Sometimes a discovered pattern may happen by chance and finding the association may be time consuming and expensive.An example of association discovery is market-basket analysis, it also is a benefit to businesses because it can allow the business to offer the products that customers will buy when buying another product, and can be used for promotions and new products (Two Crows Corp, 1999).

If in the past a customer bought soda and hot dogs at the same time, the business can have a special on hot dogs and then be able to promote a new flavor or bottling option for soda and the customer should buy both and the business will make a profit and benefit from the association discovery by having both products offer at the same time.Web MiningWeb mining can be defined as the analysis of data compiled with use of the internet, every e-mail, website, search engine, and every transaction made on websites. It can be referred to as web-content mining or web-usage mining, the difference is mining is mining the actual website sites and usage is analyzes the accesses made to the websites and the activities done on the sites (Turban & Volonino, 2011). The benefits that can come from web mining are that businesses can see what type of customer does what type of action on the site and they can offer more products or services like those that were used. For example, Best Buy can use web mining to see what customers utilize the shopping on the website and offer those specific customer free shopping for their next purchase. Or they can offer certain customers with more coupons or savings if they see that the customer has not accessed the website in a while and they think that they may lose the customer.

ClusteringClustering is when the data that is collected is separated into different categories. The reason for clustering is to find categories of customer that have similarities (Two Crows Corporation, 1999). Clustering analysis divides a market into different categories of customers where any category can be selected as a market target to be reached with a different marketing mix. This type of analysis finds clusters of data items that are related in some sense to one another and divisions that data. (Oracle.

com, 2008)Reliability of Data Mining AlgorithmsData mining is only as reliable as the information that is entered, and the way the information is presented. Data mining algorithms are queries that are used to show inclinations and trends ("What are data," ). There are several types of data mining algorithms; classification, regression, segmentation, association, and sequence.Data mining algorithms can be trusted if the data being inserted is trusted. If the data is known to be reliable data then the algorithm output will be reliable.

Some errors can be that the wrong information or specials can be sent to the wrong customer and it will go to waste. For example, in some algorithm somewhere, I am listed to either be pregnant or have a baby, which is very incorrect. In the mail I receive multiple baby promotions, coupons, announcements, and magazines. All that happens is I throw it all in the trash or the recycle bin. The company that is responsible for sending me these items is wasting their resources and annoying me.

So if I ever become in the need for baby items I certainly won’t be getting them from this company.Privacy ConcernsThere are several privacy concerns when it comes to data mining and some customers have these concerns and are not open to data mining. One concern is that personal medical information can be accessed by non-authorized personal. Which is a valid concern. Sometimes data can be unsecure and people get the information who aren’t supposed to have it. To prevent this, the number of people that have access to the data can be limited, security on the information systems that the data is stored can be enhanced, and they can limit the amount of data that is given.

Another concern from people about data mining is that companies can sell their information to third parties. This is a valid concern, companies have been known to sell a customer’s information to a third party. Now because it has been such a major concern before taking a customer’s information the company gets permission to give it to a third party, and if they don’t permission the company can’t share the information. Another concern can be the customers are being monitored by the government.

This is a valid concern because it has been proven that the government has monitored citizens in the past.Companies that Benefit from Predictive AnalysisBlue Cross and Blue Shield System (BCBS) is a company that is developing considerable benefits from predictive analysis. As an organization that provides healthcare insurance to nearly one in three Americans, BCBS has amassed a huge amount of claims-related data over the years. By applying predictive analytics technologies to its huge amount of claims data, BCBS has been getting better at not only identifying the risk factors that lead to several chronic diseases, but also identifying individuals who are at heightened risk of getting such diseases (Vijayon, 2011)Chase Bank is another company that reaping benefits from predictive analysis. Not only has it benefitted the company but the customer also. Chase was able to give a customer a better mortgage rate because they were a good customer.

Chase suggested the new mortgage rate based on the data that was analyzed from them and it showed that this customer was a good customer that deserved something special. Chase can also use the data to fight against fraud. When the bank notices activity on an account that is not normal they can give the customer a call and see if it was them.