Data mining is also known as Knowledge Discovery in Databases (KDD). Data mining is the process of automatically searching large volumes of data for patterns. Data are given from the word, the plural is derived. Data from a class of many important decisions, the measurements or observations of variables. Data-mining work in computational techniques from statistics, machine learning and pattern recognition.
Data mining process is the key that helps companies better understand their customers. Data mining can be seen as "the nontrivial extraction of implicit, previously unknown and potentially useful information from data" and are defined as "the science of extracting useful information from large quantities or databases." Data mining is interpreted differently in different contexts, but usually it is in a business or other organization, be used to recognize the need to identify trends.
As with gold mining, data mining navigation of large databases and extracts a wealth of customer data that is then translated into useful and predictive information. A prime example of data mining is its use in a distribution where a business is the purchase of a customer who buys in cotton trousers. The data mining system is an association with the customer and cotton trousers, and can either sell directly or sell the cotton trousers that customers or trying to get their clients a wide range of products to buy. Data mining also enables automatic detection of patterns in a database and guide marketing professionals a better understanding of customer psychology.
Data mining software allows users to analyze large databases to provide solutions to business decision problems. Data mining is a technology and not a business solution, such as statistics. The data mining software uses the information in a historical database of previous interactions with customers and other aspects, such as age, ZIP code, their feedback, etc. Thus, stored are the data mining software, a picture of the customers would be fascinated by the new product. This allows the marketing manager to select appropriate target customers.
Data mining is also analyzed to privacy in particular with regard to the connected data source. For example, an employer can screen out people with diabetes or a heart attack and create ethical and legal issues and the elimination of the cost of insurance. In addition to these data mining is also in the field of medicine to the combination use of drugs with harmful results.
Data mining is to be interpreted as indicating favorable results. If the data collected individuals connect on the issues of privacy, law and ethics.
Data mining can bring accuracy to drop. The creation of large central storage of customer data to all throughout the enterprise are increasingly used, but the data warehouses are not useful if no valid applications in access to and use of data companies.
Many Fortune 1000 companies worldwide have actually many data mining and campaign management installed.