What is the mining of privacy data?

Privacy data mining is the process of engaging in data for data mining without exposing confidential details concerning the information contained in one of the mined databases. Traditionally, it is used when an individual or organization works with industry competitors. While competitors can sometimes benefit from resource sharing, all parties are involved in maintaining potentially private or confidential information about their current projects. Data mining in personal data protection protects the confidentiality of all parties by bringing data mining results without actually publishing the source of any specific information.

Data mining is the process of receiving a large cluster of data and scanning for overall trends. One of the basic examples of data mining would be to see a sales database that would find out what seasons the sale of a particular product is the highest. Business Intelligence derived from this mining BY POPY Create Sale at Outside Time and make additional ÚPRAva to increase their gross profits. Another more complicated example would be scanning through databases for consumer trends in the purchase decision. This would allow manufacturers to accurately predict what types of products are becoming popular, allowing them to know where to focus their limited resources.

By associating information stored in the database with information stored in the databases competitors, the efficiency of the data mining is drastically increases. The more data it is to study, the easier it is to find and use trends. In other words, when individual organizations have 10,000 examples from which they can draw, they can usually catch formulas that would not only be evident with only 100 examples of the same type. Naturally, however, there are always some information companies that are reluctant to share with Tědic competitors. This is where data mining in personal data comes into play.

preserving privacyData mining data allows competitive companies to feed only data that they want to share in the central "municipal" database. By limiting data mining to strict voluntary information, privacy is maintained on both sides without undermining the central purpose of data mining efforts. Personal data protection can also be protected by using the impartial intermediary party to carry out actual mining, which allows companies to associate its database resources without one company has direct access to the private types of the other company.