How to Keep the Data Miners From Overwhelming the Organization Thesis

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¶ … Data Miners From Overwhelming the Organization

Data mining is not new, but the ways in which it is used are changing. There are more and more companies today that are interested in getting the 'hidden' information from their databases, but they can become confused about what they are really looking for and whether that information can tell them anything that they actually need to know. There is, naturally, a lot of interest for some people in finding out whether there are important pieces of information locked away in the data that they have already painstakingly collected. The patterns that might be there but are not now seen could tell them a lot of interesting things about their customers or their potential customers. It could also serve to tell them why some people will not be their customers and want only to shop at other places instead.

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Where survey work is concerned there can also be important issues to address in the field of data mining. If there is a lot of information collected for a study, it is possible that data holds the key to other interesting concepts that will help that study or another one that is on a similar topic. Naturally, there are no guarantees that this will be the case, but it is generally thought to be worth a try. Extracting that data is not always easy, however, and one has to know how to search. It can be risky in the sense that it can easily cost a lot of time and money to pull this data from a large database. There is also the chance that there might be sensitive information found within that database, and that would be problematic for people who did not want that information uncovered or who did not intentionally give that information to someone for the purpose of extracting it and using it elsewhere.

Overwhelmed with Data Mining

Thesis on How to Keep the Data Miners From Overwhelming the Organization Assignment

The process of data mining itself is relatively simple. An algorithm is written that will pull information that otherwise would not be easily noticeable. This information has to be in the database, of course, but it is often 'hidden.' This means that it would not come up under a regular search, since it is not set in any of the parameters that the regular search entails. This does not mean that the information is classified or sensitive in a way that could be a problem - although this is possible. Mostly it means that it gives companies another way to study market trends and demographics that they might not have otherwise been able to study or that they might have otherwise had to pay a lot of money to collect through surveys or other means. The problem with data mining, though, is that it can quickly become overwhelming.

There is so much information hidden in there, and how to get it out is something that fascinates a lot of people. Once one gets it out, what does one do with it? That is another question that can be very difficult to answer, and it can require some visualization that not a lot of people are ready for or comfortable with. This is one of the truest examples of the idea of 'thinking outside the box.' People who are 'in the box' thinkers will likely not have a lot of use for data mining because they feel as though there is not anything there that could help them out. They are strictly logical, and they do not want to mess around with data mining and get a lot of information that they do not think would tell them anything important. For people who do not always want to think inside of the box in their businesses, though, data mining can be both a blessing and a curse.

It is a blessing because it can give them a lot of fresh new insight into relationships between variables that they might not have otherwise ever noticed. It is a curse because it is easy to overwhelm a person or a business with all the data that can potentially be mined. So, how does one keep data miners from overwhelming his or her organization? By understanding what data mining can and cannot do, and by setting limits and rules as to how much data mining will play into the organizational strategy of the company. All companies should have strategies that they live by, and if they do not have these yet, they should be working on them in order to ensure that they are in place. Data mining can certainly have a place in any organization, but only if the people who are operating that organization understand both the value of it and the limitations that it has.

Risk Management and the Organization

One of the main issues for an organization when it comes to data mining is risk. If a company does not recognize the risks that come along with data mining and only focuses on the benefits, becoming overwhelmed is quite possible. Data mining can be risky for the company that does not know how to use it properly, and this is true in two ways. First, if a company has a lot of useless information extracted and then tries to make use of it, it is very easy to get off track and have problems. Second, if a company gets information that it thinks is good and then tried to use that information all at once by making major changes, that can also be very detrimental. Data mining must be seen as another tool in the arsenal of business, and not at the only tool that will work or that will be worthwhile. Overusing the idea of data mining and not making use of the information that is already easily available in the database is a huge mistake and a huge risk for any business.

Businesses that do not want to be overwhelmed by data mining have many other tools and ideas that they also use to ensure that their company runs smoothly and that the customers that they target are the right ones. Data mining can be beneficial in this, but only if it is done correctly and the information that it produces is verified to ensure that the proper information was extracted from it. If it indicates that the demographics in a particular city or area of the country have changed, that is worth knowing. It is also worth knowing if there are large, untapped areas that the company might be able to move into. There is certainly risk involved there, but in that case the data mining is just the first step in a larger investigation of whether moving into that area would be a good choice.

When used that way, it will not overwhelm the organization with either useless information that the company cannot use or so much useful information that the company becomes bogged down while trying to determine which parts of it would be best to use. Unfortunately, most companies do not manage their risks that well, especially when they come from the inside or when they are not correctly perceived as risks. Data mining, because it can be so beneficial to an organization that uses it correctly, is often ignored as being a risk for companies. When they manage risk they tend to look at all kinds of other issues, but they avoid that one because they simply do not see it. Only once it has become a problem through the misuse of information or through becoming overwhelmed with information do companies start to realize the significance of having a problem with data mining.

The worst case scenario for a company in this predicament would be an avalanche of data mining information to sort through and then the making of the wrong decision due to a misinterpretation of the data or to a lack of understanding about what was really searched for and found. It could be disastrous for a company, and all because it allowed data mining to become overwhelming and cause a problem. A key to avoiding risk within an organization is to stop data miners from doing these kinds of things.


There is no question that data mining is important, but when it comes to how to keep the data miners from overwhelming the organization, one thing is clear: data mining must be only one tool that the company uses. It is not necessary, nor is it wise, to put all one's eggs in one basket, but that is what many companies do with their data mining. Especially when they start to struggle just a little bit with some aspect of their marketing or sales, they tend to panic and assume that they have to do something drastically different. In reality, they might only need to make some small changes, and there are many ways to take a look at the organization and see if there is something different that… [END OF PREVIEW] . . . READ MORE

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How to Keep the Data Miners From Overwhelming the Organization.  (2008, October 18).  Retrieved January 18, 2021, from

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"How to Keep the Data Miners From Overwhelming the Organization."  18 October 2008.  Web.  18 January 2021. <>.

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"How to Keep the Data Miners From Overwhelming the Organization."  October 18, 2008.  Accessed January 18, 2021.