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Data mining can uncover interesting patterns. Some cookies will upload solely for the purpose of data mining.
Data mining is the process of extracting hidden patterns from data. As more data is gathered, with the amount of data doubling every three years,[1] data mining is becoming an increasingly important tool to transform this data into information. It is commonly used in a wide range of profiling practices, such as marketing, surveillance, fraud detection and scientific discovery. Database is just the system that holds all the data. Or: "A database is a structured collection of records or data that is stored in a computer system." http://en.wikipedia.org/wiki/Database http://en.wikipedia.org/wiki/Data_mining
data warehouse A data warehouse is the main repository of an organization's historical data, its corporate memory. It contains the raw material for management's decision support system. The critical factor leading to the use of a data warehouse is that a data analyst can perform complex queries and analysis, such as data mining, on the information without slowing down the operational systems. data mining The development of computational algorithms for the identification or extraction of structure from data. This is done in order to help reduce, model, understand, or analyze the data. Tasks supported by data mining include prediction, segmentation, dependency modeling, summarization, and change and deviation detection. Database systems have brought digital data capture and storage to the mainstream of data processing, leading to the creation of large data warehouses.
difference between Data Mining and OLAP
The term data mining is generally known as the process of analyzing data from many different perspectives in order to correctly organize the data. Sometimes data mining is also called knowledge dicovery.