Business intelligence data mining is a process of using sophisticated equipment to locate and extract relevant business information from a larger body of data. The term is also sometimes associated with the retrieval of data that is stored in a damaged device, such as on a server or computer hard drive that has crashed. This form of data mining seeks to access necessary data that relates to the history and current standing of a business enterprise, and allow that data to be arranged in a logical fashion.
In most situations, business intelligence is understood to be information that has to do with the overall function of a company. This can include information like financials, client lists, policy and procedure documents, shareholder registers, and even electronic copies of contractual agreements with customers and vendors. With a data mining tool, it is possible to conduct a focused search for data that is needed, rather than having to pore through all the stored data manually. When there is a need to locate and reference specific information in a short period of time, business intelligence data mining is the most efficient process.
Along with locating and extracting data for use in some type of evaluation or upcoming project, business intelligence data mining can also be utilized in an emergency situation. For example, if some type of natural disaster renders a company server inaccessible, this form of data mining may be used as a means of rescuing the stored data from the damaged piece of equipment. In this application, the server is subjected to a number of tests in order to locate any nodes in the memory that are still functional, and use various means to copy that data from the damaged drive. At that point, the extracted data can be reordered into some sort of logical sequence, and reloaded onto a new server. While business intelligence of this type can be somewhat expensive, the time and expense saved in recreating the lost data using hard copy documents often exceeds the cost of the extraction.
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Just as business intelligence data mining can be used for constructive reasons, the strategy can also be employed as a means of causing damage to existing data. With this application, key data is located, extracted, altered, then substituted for the original information. Often, the goal of this type of activity is to create a false image of the financial background of a business or individual, either as an attempt to discredit the data owner, or to remove evidence of some type of questionable or unethical transactions conducted by one or more individuals within the company framework. Depending on the quality of the business intelligence data mining that is conducted, it may be virtually impossible to identify the changes made, unless the original data was copied and stored in a location that was not accessible to the data miners.