Data management, data warehousing, and data mining

¶ … Management - Data Warehousing and Data Mining

Data Management: Data Warehousing and Data Mining

Data management is very important to any business. No matter how much data is collected, it is what is done with the data once it has been collected that can make or break an organization. Obviously the data should be kept safe, but there is more to the mining and warehousing of data than just protecting it. If data is simply collected and nothing is done with it, that data is relatively useless to the company. One of the most important issues with data management is making sure that the data mining and warehousing systems that are used in an organization do not become more trouble than they are actually worth. How can that be done in the best way possible? The answer to that question can vary greatly, depending on who is asked. Even the same researcher can make cases both for and against the warehousing of data in an organization (Greenfield, 2005a; Greenfield, 2005b).

Because it is possible to collect so much data on people today, many individuals who use the internet are being tracked more than they realize (Betancourt, 2010). When they talk with their friends over social media sites and share their likes and dislikes, tracking cookies and analytical programs are collecting that information. In most cases the information is not tied to the names of the people. It is just used in order to look for trends and see what is popular and what is not. In some cases, however, the behaviors that a person engages in online can be tracked back to that specific person. That is an important distinction, and one that most people are unclear about because they do not realize just how much of their personal and (seemingly) private browsing history and other information is being collected and used by companies (Thearling, 2009).

Once the data has been "mined" from social media sites, browsers, and sites that are visited by internet users, it has to be "warehoused" (i.e. stored) somewhere. There is no physical location needed for data in the sense of papers and other documents, but there is often such a large amount of data that it must be stored on large computers that do take up space. These need to be carefully maintained. If they are large enough, they also need to be in a strongly climate-controlled environment, because they will put off enough heat that they could overheat and become damaged. There are many different ways to store and use the collected data, depending specifically on how much is being collected and the overall plan of the company that is collecting it.

Companies that do not use any kind of data warehousing and mining know very little about their customers. That is why companies must focus on accumulating data that will help them better understand their target market while cutting down on wasteful expenditures of advertising (Hadfield, 2009). Many companies are already starting to do this, and companies that are not are falling behind their competitors. If a company does not know who is buying from them and why their products or services appeal to those particular individuals, it can be hard to determine what they should do to increase sales and keep customers coming back for more. Because of that, data mining and warehousing should be used in order to help businesses get ahead and keep up with their competitors. At times, though, data mining and data warehousing can become more trouble than they are actually worth, and that can lead to all types of problems for a company (Thearling, 2009).

In order to make sure that data mining and warehousing do not become too much trouble for a company to handle, it is vital that the company is clear on the data it wishes to collect. There is no reason to collect every single scrap of data from every person who uses the company's website or searches the internet for the product or service that the company offers. Basic demographic information that relates to the company's product or service, or that relates to the creation of a target market segment, is all very important (Greenfield, 2005a. There are many other data markers that are outliers, however, and that will not have any effect on whether a person would use what the company has to offer. When those data markers are also collected, it can become easy for a company to get overwhelmed by the information coming in (Greenfield, 2005b).

Sorting out the important data from the unimportant data is something that must be done at the very early stages of data mining (Thearling, 2009). Then, only the significant data that the company actually needs can be warehoused and used as needed. That is the best way to collect, store, and use any data that a company can benefit from. Companies that use data warehousing must reduce the amount of data that they store and the length of time they keep that data, or they run the risk of simply becoming overwhelmed with information that they really are not using and that they are not able to do anything productive with. Avoiding that kind of problem is not always easy, but it is certainly worthwhile for any company no matter the industry in which that company is involved.