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  2. Data mining - Wikipedia

    en.wikipedia.org/wiki/Data_mining

    Before data mining algorithms can be used, a target data set must be assembled. As data mining can only uncover patterns actually present in the data, the target data set must be large enough to contain these patterns while remaining concise enough to be mined within an acceptable time limit. A common source for data is a data mart or data ...

  3. Examples of data mining - Wikipedia

    en.wikipedia.org/wiki/Examples_of_data_mining

    One data mining method that is used to perform this task is known as multifactor dimensionality reduction. [15] In the area of electrical power engineering, data mining methods have been widely used for condition monitoring of high voltage electrical equipment.

  4. Data analysis - Wikipedia

    en.wikipedia.org/wiki/Data_analysis

    Data mining is a particular data analysis technique that focuses on statistical modeling and knowledge discovery for predictive rather than purely descriptive purposes, while business intelligence covers data analysis that relies heavily on aggregation, focusing mainly on business information. [4]

  5. Cross-industry standard process for data mining - Wikipedia

    en.wikipedia.org/wiki/Cross-industry_standard...

    The Cross-industry standard process for data mining, known as CRISP-DM, [1] is an open standard process model that describes common approaches used by data mining experts. It is the most widely-used analytics model.

  6. Text mining - Wikipedia

    en.wikipedia.org/wiki/Text_mining

    Text mining, text data mining (TDM) or text analytics is the process of deriving high-quality information from text. It involves "the discovery by computer of new, previously unknown information, by automatically extracting information from different written resources." [1] Written resources may include websites, books, emails, reviews, and ...

  7. Educational data mining - Wikipedia

    en.wikipedia.org/wiki/Educational_data_mining

    Data is also distilled for the purposes of classifying features of data, which for educational data mining, is used to support the development of the prediction model. Classification helps expedite the development of the prediction model, tremendously.

  8. Data farming - Wikipedia

    en.wikipedia.org/wiki/Data_farming

    Data farming is the process of using designed computational experiments to “grow” data, which can then be analyzed using statistical and visualization techniques to obtain insight into complex systems. These methods can be applied to any computational model. Data farming differs from Data mining, as the following metaphors indicate:

  9. Data management - Wikipedia

    en.wikipedia.org/wiki/Data_management

    There are 2 main categories of data analysis tools, data mining tools and data profiling tools. Also, most commercial data analysis tools are used by organizations for extracting, transforming and loading ETL for data warehouses in a manner that ensures no element is left out during the process (Turban et al., 2008).